WatchMe: Utilizing Digital Tools to Improve Patient Education, Satisfaction and Attendance in the Echo Stress Laboratory

PROJECT LEAD(S):

Aimee Camano MSN FNP-C

William Bradley DNP

EXECUTIVE SPONSOR(S):

Isaac Kwan - Cardiac Sonographer, Supervisor

Dr. Kirsten Fleischmann -  Associate Chief of Cardiology, Ambulatory Operations

Monet Strachan - Technical and Quality Director, Adult Echocardiography

Dr. Mike Salerno – Echo Laboratory  Chief Medical Director, Cardiology

ABSTRACT  

Heart disease remains the leading cause of mortality in the United States affecting both men and women (Centers for Disease Control and Prevention, 2024). At UCSF, a range of cardiac stress tests – including Treadmill Stress Echo, Stress EKG Test, Supine Bicycle Stress Echo, Dobutamine Stress Test and Tilt Table Testing – are essential diagnostic tools for preventing heart attack and progression of cardiovascular diseases. However, these tests currently face a scheduling wait time of 1-2 weeks, with daily patient cancellations, reschedules and no-shows at 10.2% contributing to an estimated annual revenue loss of $1,861,779. 

The primary causes of missed appointments leading to revenue loss include patient refusal, inability to follow instructions when holding beta blockers due to limited understanding of the tests, inappropriately ordered test due to acute disease conditions such as musculoskeletal limitations and uncontrolled hypertension. To address these challenges, developing a digital education tool partnering with Mytonomy, a contracted media company, tailored specifically for UCSF echo procedures and digitally updating our stress laboratories by placing television sets in the waiting room and individual stress rooms will improve patient education, satisfaction, and reduce missed appointments. This tool will be integrated in the Echo Lab website and embedded within the Epic system, allowing providers and patient care teams to shared decision making by providing real-time educational resources with patients at the point of care. This informative and collaborative approach to ordering tests, encourages patients engagement thereby increasing the chance of patients showing up for the appointment. In the primary setting, a systematic review by Coronado-Vasquez et al., shows  strong evidence supporting use of decision aids in improving knowledge, risk and patient satisfaction in their plan of care (2020). 

Following implementation, a targeted campaign: WatchMe is designed to raise awareness about the digital platform available to the UCSF community. The  impact will be measured by analyzing Epic data and Press Ganey Patient Satisfaction scores in six months post-intervention. By enhancing patient education and provider support, WatchMe aims to improve clinical accessibility, reduce delays in critical cardiac testing necessary for early diagnosis and treatment of heart disease, and mitigate revenue loss- ultimately advancing patient care and operational efficiency at UCSF.

TEAM 

Aimee Camano MSN FNP-C- Nurse Practitioner

William Bradley DNP, ACNP Nurse Practitioner

PROBLEM  

Over the past six months, the UCSF Parnassus Echocardiography (Echo) Lab has experienced a 10.2% daily average  patient cancellations, reschedules, or no-shows. This trend has adversely affected scheduling efficiency, revenue, and patient satisfaction. As of February 14, 2025, the average wait time for stress testing appointments is 1-2 weeks. In a similar internal study done at the UCSF Radiology Unit by Anthony et al. (2022), the initial no show rate was at 18.1%,  after calling patients two- to four days prior to scheduled appointment, the rate decreased to 4.3%. Currently, the echo lab is sending calls and text messages prior to appointment and the no show rate from August 19, 2024 to February 14, 2025, a total of 122 working days remains at 10.2%.

A significant contributor to these missed appointments includes orders that do not correlate to patient’s physical condition prior to testing such as mobility limitations, uncontrolled hypertension and receiving beta blocker treatment. Moreover, patients' limited understanding of procedures, leading to unmet expectations and test changes, is reflected in the 2025 PressGaney score of 94.3% for staff's explanations. Consequently, more time is needed to describe the procedures leading to increased waiting time in registration,shown at 92.91% (PressGaney, 2025). These factors lead to delays, rescheduling, or cancellations, thereby impacting future scheduling availability and revenue. Overall, the likelihood to recommend stress testing is at 55th percentile with a decrease in trend since 2021 (PressGaney, 2025). 

TARGET

The primary beneficiaries of this project are patients aged 18 to 90 scheduled for cardiology stress testing. Our goal is to reduce missed testing opportunities from 10.2% to less than 5% within six months by improving access to educational resources while fostering collaborative decision making when test ordering. Data will be collected by tracking no-shows, cancellations, and rescheduled tests, aiming to enhance outpatient and inpatient access to cardiac stress testing. Furthermore, the echo lab team seeks to improve patient satisfaction by decreasing the wait time in registration and improve likelihood to recommend.

Table 1. Collected Data from 8/19/24- 02/14/25

Table 2. Cost of Studies 2025 - Average Cost of Procedures Billed  $5,881

 Table 3. RETURN ON INVESTMENT (ROI) – $857,879

 GAPS

Due to time constraints during clinic visits, patients often struggle to comprehend and visualize the procedures. The current age for stress testing is over 65 years old, with diverse educational backgrounds and language proficiencies. Providing educational videos in multiple languages with clear visual demonstrations will enhance equity and accessibility for all patients.

 INTERVENTION 

 Developing a digital educational tool by partnering with Mytonomy focusing on UCSF-specific echo procedures such as Treadmill Stress Echo, Treadmill Only, Supine Bicycle Stress Echo, Dobutamine Stress Test, and Tilt Table Testing. Existing educational guidelines and protocols will enhance accuracy in creating videos available in the following platforms: Epic system (while ordering), MyChart for patient access, and UCSF Echocardiology website. Once the videos are produced, a robust campaign (WatchMe) emphasizing ease of access to multiple clinic sites within UCSF will start and continue until the 6^th month. Utilizing a multi-channel communication through emails, intranet, posters and creating events in major outpatient clinics in UCSF to hold Q&A sessions while showing videos of our stress laboratory.  A digital upgrade to install television and other electronic devices (IPAD) will then be utilized at the exercise lab to show the video to patients. At this stage data collection will commence to document missed opportunities and patient satisfaction for comparison. 

PROPOSED EHR MODIFICATIONS

• Integration of Video Links: Incorporate video links into stress testing order forms within the Epic system which will then be available in MyChart for patients to view.
• Enhanced Ordering Process: Add prompts to provide real-time information to providers and patients regarding the ordered tests.
• Updated Online Resources: Revise the UCSF Echo Lab website to include access to frequently asked questions and educational materials.
• Update the digital tools at the echo lab with television sets and other digital tools (IPAD).

SUSTAINABILITY and SCALING

 The videos wil be available to UCSF with Mytonomy licensing for two years. Since the video links will be automatically embedded in the EPIC system when orders are placed, all providers including care teams have access to this digital educational tool, strengthening shared decision making and engagement in the testing modality. The project can scale up to all exercise labs in the UCSF system including remote sites. Team meetings will be held monthly to address barriers, successes and adjust strategies to sustain momentum. The same model can be replicated in multiple procedural areas within the UCSF system to improve missed opportunities for testing. Furthermore, potential research opportunities in measuring exercise capacity with digital tools to improve exercise time will be available in the future. 

 Table 4. BUDGET - Projected Cost $50,000

References

Anthony, R., Fleischman, K., Bradley, W., Chao, C., Lee, S., Greenway, J. (2022). Myocardial Perfusion Study No Show Rate.

Coronado-Vázquez, V., Canet-Fajas, C., Delgado-Marroquín, M. T., Magallón-Botaya, R., Romero-Martín, M., & Gómez-Salgado, J. (2020). Interventions to facilitate shared decision-making using decision aids with patients in Primary Health Care: A systematic review. Medicine, 99(32), e21389. https://doi.org/10.1097/MD.0000000000021389

Centers for Disease Control and Prevention. (2024, October 24.). Heart Disease Facts. https://www.cdc.gov/heart-disease/data-research/facts-stats/index.html

 PressGaney. UCSF Echo Lab Parnassus. (2025, February 21).  Breakout Scorecard.

tests were sent in 2022, 255 in 2023, and 614 in 2024 (Figure 1), leading to a total cost in 2024 estimated >$1 million at approximately $2,200/test (Figure 1; Appendix 3). 34 tests have been

Figure 1. pmNGS volume and cost at UCSF are increasing sharply. Left panel: Volume of pmNGS tests sent at UCSF since the test introduction (black line), % of tests with at least one microbe detected (blue line) and % of tests with high-pathogenicity organisms detected (green). Right panel: estimated cost of pmNGS testing per year. 2025 is projected by # tests sent from 1/1/25-1/17/25 and 2024 per-test cost.

Sources Cited

1. Chiu CY, Miller SA. Clinical metagenomics. Nat Rev Genet 2019;20(6):341-355. DOI: 10.1038/s41576-019-0113-7.
2. Wilson MR, Shanbhag NM, Reid MJ, et al. Diagnosing Balamuthia mandrillaris Encephalitis With Metagenomic Deep Sequencing. Ann Neurol 2015;78(5):722-30. DOI: 10.1002/ana.24499.
3. Madut DB, Chemaly RF, Dadwal SS, et al. Clinical Utility of Plasma Microbial Cell-Free DNA Sequencing Among Immunocompromised Patients With Pneumonia. Open Forum Infect Dis 2024;11(8):ofae425. DOI: 10.1093/ofid/ofae425.
4. Hogan CA, Yang S, Garner OB, et al. Clinical Impact of Metagenomic Next-Generation Sequencing of Plasma Cell-Free DNA for the Diagnosis of Infectious Diseases: A Multicenter Retrospective Cohort Study. Clin Infect Dis 2021;72(2):239-245. DOI: 10.1093/cid/ciaa035.
5. Vinh Dong H, Saleh T, Kaur I, Yang S. Elucidating the Clinical Interpretation and Impact of a Positive Plasma Cell-Free DNA Metagenomics Test Result-A Single Center Retrospective Study. J Appl Lab Med 2024;9(1):14-27. DOI: 10.1093/jalm/jfad083.
6. Shishido AA, Noe M, Saharia K, Luethy P. Clinical impact of a metagenomic microbial plasma cell-free DNA next-generation sequencing assay on treatment decisions: a single-center retrospective study. BMC Infect Dis 2022;22(1):372. DOI: 10.1186/s12879- 022-07357-8.
7. Bergin SP, Chemaly RF, Dadwal SS, et al. Plasma Microbial Cell-Free DNA Sequencing in Immunocompromised Patients with Pneumonia: A Prospective Observational Study. Clin Infect Dis 2023. DOI: 10.1093/cid/ciad599.
8. Benamu E, Gajurel K, Anderson JN, et al. Plasma Microbial Cell-free DNA Next- generation Sequencing in the Diagnosis and Management of Febrile Neutropenia. Clin Infect Dis 2022;74(9):1659-1668. DOI: 10.1093/cid/ciab324.
9. Schulz E, Grumaz S, Hatzl S, et al. Pathogen Detection by Metagenomic Next- Generation Sequencing During Neutropenic Fever in Patients With Hematological Malignancies. Open Forum Infect Dis 2022;9(8):ofac393. DOI: 10.1093/ofid/ofac393.
10. Kalantar KL, Neyton L, Abdelghany M, et al. Integrated host-microbe plasma metagenomics for sepsis diagnosis in a prospective cohort of critically ill adults. Nat Microbiol 2022. DOI: 10.1038/s41564-022-01237-2.
11. Langelier C, Kalantar KL, Moazed F, et al. Integrating host response and unbiased microbe detection for lower respiratory tract infection diagnosis in critically ill adults. Proc Natl Acad Sci U S A 2018;115(52):E12353-E12362. DOI: 10.1073/pnas.1809700115.
12. Wilson MR, Sample HA, Zorn KC, et al. Clinical Metagenomic Sequencing for Diagnosis of Meningitis and Encephalitis. N Engl J Med 2019;380(24):2327-2340. DOI: 10.1056/NEJMoa1803396.
13. Gu W, Deng X, Lee M, et al. Rapid pathogen detection by metagenomic next-generation sequencing of infected body fluids. Nat Med 2021;27(1):115-124. DOI: 10.1038/s41591- 020-1105-z.

PROPOSAL TITLE: Improving Health and Tech Literacy by Optimizing MyChart usage through a Student Patient Navigator Program  

PROJECT LEADS:
Helen Lau RN CPNP – Craniofacial Pediatric Nurse Practitioner
Jaclyn Kukoff SLP – Speech Pathologist

PROBLEM  

• This is a particularly salient problem in our ever-changingtechnological world. We plan to leverage technology to help improve patient autonomy and care. We also serve a diverse population and would like to decrease disparities in health and tech literacy.  

TARGET   

MEASURABLE PROGRAMMATIC GOALS  

Our visits in the Craniofacial Center can last anywhere from 15 min for a post op appointment to 60 min for a new patient with complex needs.  Frequently, there is not enough time to review how to download or use MyChart during the visit or the parents are in a rush to leave the hospital/clinic.    

Although there is a handout that details how to download MyChart which may be given to the family at the registration desk, parents continue to have difficulty following the instructions on how to get started with MyChart especially with parent identification as a proxy. Within our center, we do try to review how to download the app as much as we can however, the decreased number of families who log in compared to downloading the app show that parents are not effectively utilizing MyChart.  

INTERVENTION 

PROPOSED EHR MODIFICATIONS N/A

RETURN ON INVESTMENT (ROI) 

SUSTAINABILITY 

BUDGET  

PROJECT LEADS: Rebecca Carter, MD, Vidya Pai, MD, Clare Pearson, RN, CNL

EXECUTIVE SPONSORS: James Anderson, MD, Director of Neonatology, UCSF Benioff Children’s Hospital Oakland, Leslie Lusk, MD, Medical Director, ECMO Co-Medical Director, UCSF Benioff Children’s Hospital Oakland 

ABSTRACT: Mother’s own milk (MOM) is the optimal nutrition source for critically ill infants. Provision of MOM is associated with reductions in many short- and long-term neonatal morbidities. Use of MOM is associated with both direct and indirect cost savings through reduction in subsequent healthcare utilization and improved neurodevelopmental outcomes. Benioff Children’s Hospital (BCH) Oakland neonatal intensive care unit (NICU) discharges fewer infants on MOM than other safety net NICUs in California. Without regular lactation support from a dedicated NICU International Board-Certified Lactation Consultant (IBCLC), our NICU has struggled to increase rates of breastfeeding and MOM use. We propose the introduction of regular lactation support to help mothers establish and maintain milk supply, and the initiation of an oral milk drops procedure to provide MOM to all infants on day-of-life 3 until ready for oral feeding. Through this intervention, we will increase the rates of breastfeeding and MOM use at time of NICU discharge and reduce length of NICU hospitalization by ≥1 day in at least 30% of NICU admissions. Based on a variable direct cost of $3,154/day, and an average of 393 yearly admissions from 2022-2024, we estimate a direct cost savings of $369,018 for FY2026. Because the benefits of MOM feedings far exceed these measurable direct cost benefits, we expect the financial savings to the healthcare system to greatly exceed this estimate. Additional benefits include cost savings from reducing donor human milk and formula use; decrease in short- and long-term neonatal morbidities; reduction in rehospitalization rates and pediatric subspecialty visits; and improved patient and family experience through enhanced bonding. This intervention aligns with the True North Pillars of improving clinical outcomes, improving financial performance, and creating exceptional patient experiences.

TEAM: Rebecca Carter, MD, Project Lead; Vidya Pai, MD, MS Epi, Project Lead; Clare Pearson, RN, CNL, Nursing Project Lead; Manchen Hao, MPH, PMP, Quality Improvement Advisor; Taranae Mahmoodi, Neonatology Service Line Director; Phuong Huynh, RD; Vanessa Kobza, RD; Leslie Lusk, MD, Medical Director, Neonatology, UCSF Benioff Children’s Hospital Oakland

PROBLEM: Mother’s own milk (MOM) is the optimal nutrition source for critically ill and premature infants. When provided during a critical exposure period in the NICU hospitalization, MOM is associated with a reduction in many short-term neonatal morbidities including late onset sepsis, necrotizing enterocolitis, chronic lung disease, and retinopathy of prematurity.^1,2 Dose-dependent effects of human milk feeding have been demonstrated to improve cognitive and language development,⁴ and reduce healthcare utilization through fewer hospitalizations, pediatric subspecialty visits, and specialized therapy supports after NICU discharge.⁵ Estimated costs of these prematurity-related complications that may be avoided with MOM use range from $27,890 for late-onset sepsis to $46,103 for necrotizing enterocolitis (in 2016 US dollars).⁶

Lactation consultants are essential resources for hospitalized newborns and their mothers. Dedicated NICU lactation support is associated with increased rates of breastfeeding and MOM use during hospitalization and at time of discharge.^7-9 Lactation support also provides direct cost savings through reduction in donor milk and formula use in addition to the previously described indirect cost savings through improved health outcomes. 

The proportion of infants receiving mother’s own milk (MOM) at time of discharge from the BCH Oakland NICU is lower than comparable safety net NICUs in California, particularly in our most vulnerable population of Very Low Birth Weight (VLBW) infants. From 2018-2022, only 42% of our VLBW babies were receiving MOM at NICU discharge, compared to 67% for comparable California safety net NICUs. Black VLBW infants fare particularly poorly, with less than 30% of Black infants receiving MOM at NICU discharge. Despite interventions to promote breast pumping and address barriers to MOM use by our quality improvement team, our rates of breast milk use are poorly sustained for the duration of NICU hospitalization. Based on input from our families and staff, the inability to provide regular and frequent lactation support is one of the most significant barriers to improving rates of breastfeeding and MOM use. 

Critically ill infants experience many invasive oral procedures, such as suctioning, taping, feeding tube insertion, intubation, and mask ventilation. These repetitive experiences can negatively impact oral function and the subsequent progression of oral feeding skills.⁹ Delayed oral feeding competence is a primary driver of prolonged NICU hospitalization, and mitigation of negative oral experiences during the period of critical infant brain development is essential to promoting feeding proficiency.^9,10 O’Rourke et al utilized lactation support to provide positive oral experiences through the provision of oral milk drops in infants unable to orally feed. They found that this low-cost intervention led to a 4-day reduction in hospital length of stay and an estimated cost savings of over $600,000, in addition to enhanced parental understanding of oral feeding and improved bonding.¹⁰

TARGET: Our goal is to establish regular lactation support for families in the BCH Oakland NICU. With the support of a dedicated IBCLC, we will provide early, regular, and frequent lactation support for breast pumping. We will partner with a local lactation service that currently supports the UCSF Mission Bay ICN and the BLOOM: Black Love Opportunity and Outcome Improvement in Medicine Clinic, to provide racially concordant lactation support to Black race-identifying families. We will provide education to staff and family on the benefits of human milk feedings and standardize and support the transition to non-nutritive breastfeeding (NNBF) and nutritive breastfeeding (NBF). For infants unable to feed orally, we will establish a procedure for families and staff to provide oral milk drops. We will utilize the electronic health record to automate interventions and track outcomes.

GAPS 

INTERVENTION 

Urgency: The American Academy of Pediatrics proposed standards for levels of neonatal care in 2023, indicating that an IBCLC be available on-site for weekday consultation and be accessible by phone 24/7.¹²With no dedicated NICU IBCLC, the BCH Oakland NICU does not meet this standard of care.

Barriers: Implementing an IBCLC and providing oral milk drops will require creation of new workflows, in addition to education and training of nursing staff. We aim to mitigate these challenges through educational sessions and in-unit training.

Possible adverse outcomes: Breast milk administration error rates will continue to be tracked and reviewed. 

Plan to measure and close equity gaps: Rates of lactation consultation, expressed milk volumes, direct breastfeeding, and MOM use at discharge will be measured for all patients and further stratified by race and ethnicity. Any identified inequities will be communicated to clinicians, and efforts to close potential gaps will be incorporated into the interventions.

PROPOSED EHR MODIFICATIONS: APeX order sets will be revised to automate orders for IBCLC consultation, oral milk drops, and eligibility criteria for NNBF. A dashboard will be created to track outcome measures and review data with key stakeholders. 

RETURN ON INVESTMENT (ROI): For FY24, the cost components for BCH Oakland NICU bed days (variable direct costs only) were $3,154 per day. The average number of NICU admissions from 2022-2024 was 393 infants. Based on a conservative estimate of length of stay reduction of 1 day in at least 30% of NICU admissions in FY2026, we estimate a direct cost savings of $3,154/day x (393 x 30%) = $369,018 for FY2026.

SUSTAINABILITY: These interventions will be sustained by the BCH Oakland NICU quality improvement team led by Drs. Pai and Carter, Clare Pearson, Phuong Huynh, and Vanessa Kobza. Outcome measures will be reviewed monthly to ensure continuous quality improvement. If the introduction of a dedicated NICU IBCLC proves to be a high-impact intervention, we will advocate to establish a permanent partnership with our local lactation services.

BUDGET: See attachment

PROJECT LEAD(S):

• Monisha Bhatia, MD – Assistant Professor, Division of Hospital Medicine
• David Arboleda, MD – Assistant Professor, Division of Hospital Medicine
• Guinn Dunn, MD – Assistant Professor, Division of Hospital Medicine
• Prashant Patel, DO – Assistant Professor, Division of Hospital Medicine

 EXECUTIVE SPONSOR(S):

• Bradley Monash, MD – Vice Chief of Clinical Affairs, Hospital Medicine
• Michelle Mourad, MD - Vice Chair of the Department of Medicine

ABSTRACT:

Securing on-time discharges improves hospital throughput and optimizes patient flow and capacity. This is especially important during times of high census and ED boarding, which have significant patient experience and safety implications. The Hospital Medicine Service (HMS) cares for the largest volume of patients at UCSF Health, but often faces challenges in securing on-time discharges. Estimated discharge date accuracy for the service was as low as 62% in 2023, while length of stay averaged 8.1 days. Discharge delay can result from (1) variability in discharge planning practice patterns among hospitalists, (2) inadequate alignment among interprofessional team members on which patients are expected to discharge, (3) insufficient communication of discharge barriers, and (4) lack of coordination on which team member will complete discharge tasks. Since October 2023, the HMS has piloted the interprofessional “Accelerated Discharge Program,” (“ADP”), designed to enhance communication of anticipated discharge and streamline coordination on discharge tasks for patients most likely to discharge the following day. The ADP team systemically collected data on common discharge barriers, developed expertise in addressing common discharge barriers and inefficiencies, improved identification of patients likely to discharge and assisted with completing discharge tasks. Length of stay improved from 8.1 to 7.4 days in the intervention group.

Through the Caring Wisely program, our interprofessional team seeks to develop a platform to communicate discharge barriers with other disciplines at the unit and the health system level through Informatics and APeX build support. We ultimately aim to increase the number of on-time discharges, reduce length of stay, and support UCSF’s global capacity optimization efforts.

TEAM:

• Brandon Scott, MD – Director of Value Improvement, Division of Hospital Medicine (DHM), Primary Project Mentor
• Rachel White, MHSA – Quality Improvement Program Manager, DHM, Program Manager
• Connie Li – Clinical Assistant, Goldman Medical Service (DHM), Team Member
• Sarah Apgar, MD – Director, Goldman Medical Service (DHM), Core Advisor
• Ethel Wu, MD – Assistant Director, Goldman Medical Service (DHM), Core Advisor
• Ongoing discussions with Medicine Case Management Leadership, Nursing Leadership and Patient Capacity Management Center Leadership on partnership and integration
• Bradley Monash, MD – Vice Chief of Clinical Affairs, DHM, Executive Sponsor

PROBLEM:

The UCSF Parnassus campus frequently experiences challenges with high capacity, necessitating focused efforts to optimize on-time discharges within inpatient care teams.  The quality, safety, and financial consequences of a lower than predicted number of on-time discharges include but are not limited to:

• Suboptimal patient satisfaction due to prolonged ED and post-anesthesia care unit (PACU) boarding
• Suboptimal care quality and risk of patient safety events, as the number of admitted patients “boarding” in the ED PACU increases 
• Significant provider burnout and moral distress due to caring for patients in the “wrong care location”
• Limitations in outside hospital transfers, interservice transfers within UCSF, and direct admissions of patients who require UCSF quaternary care
• Prolonged length of stay for admitted patients (e.g. discharge barriers not addressed earlier in the admission, adding subsequent day(s) to the patient’s hospitalization for ongoing care coordination)

For patients on the HMS, UCSF’s largest service by volume with over 7,000 Parnassus Campus discharges in 2023, many delays in on-time discharges stem from deficiencies in the care team coordination and communication processes. For example:

• HMS multidisciplinary discharge rounds (MDR) are intended to raise awareness of anticipated discharge and discharge coordination tasks but lack a structured communication method to alert other members of the interdisciplinary team and health system leaders of these tasks.
• The current workflow relies on accurate EDD to alert and prioritize core services (Case Management (“CM”), Medical Social Work, Nursing, Pharmacy, Radiology, Rehabilitation Services) when there are pending tasks for a patient expected to discharge. Inaccurate EDD misdirects resources and risks further delays to other patients more likely to discharge.
• Similarly, as the patient’s clinical condition and discharge needs evolve, we rely on CM to update EDD but there is variability in practice pattern on the frequency and detail of communication between clinicians and CM, without structured communication or feedback pertaining to changes that extended the EDD.

TARGET:

• We seek to increase the number of on-time discharges of HMS patients by improving communication of identified discharge barriers. Specific targets include:
  • Develop a method for centralized, structured communication of identified discharge barriers which is visible to multidisciplinary team members at the unit and health system level and integrates with frontline multidisciplinary team workflows
  • Leverage current Patient Capacity Management Center (“PCMC”) workflows and integrate with upcoming changes in throughput optimization efforts (via Deloitte redesign for Proactive, Timely Discharge Planning) to more proactively address discharge barriers on up to 2 days prior to EDD.
  • Through these interventions we hope to achieve further reduction in Length of Stay (LOS): We anticipate expedited discharge barrier resolution resulting in earlier discharges that will lead in an average length of stay reduction of 0.3 days.

GAPS

System issues and technological gaps include:

• Lack of centralized, structured communication of discharge barriers that can be easily updated directly by the physician caring for and ultimately discharging the patient. Care team members use different EHR-based tools to track discharge barriers (such as Discharge Milestones, Discharge Comments, the MDR Discharge Planning Tool, and structured and unstructured text in clinical notes and patient list columns), leading to compartmentalization and redundancy of information in discordant areas in the electronic health record (EHR), inaccurate EDD, and misdirection of resources.
• Inconsistent documentation of the discharge plan in primary team clinician notes or in other locations like sticky notes, discharge navigators. There is variability in documentation of the discharge plan, which we are attempting to address with standardized note templates. However, even when these fields are completed, the information is not readily available to other members of the interprofessional team and health system leadership who are attempting to expedite discharges.
• No shared understanding of the global discharge plan between disciplines despite implementation of the discharge milestones tools. Each member of the interprofessional team has access to important information that may alter the discharge plan but this information is not quickly accessible to the care team and currently requires duplication of work and additional person-to-person communication, increasing the burden of communication.

 Educational gaps include:

• Suboptimal interprofessional awareness of existing systems that can be proactively mobilized to support accelerated discharges.

INTERVENTION:

In October 2023 we initiated our Accelerated Discharge Program (ADP) pilot on the HMS’s direct care teams, which involved streamlining outreach to identify likely next day discharges, discharge barriers, and delegate specific tasks to our Clinical Assistant. ADP has developed standard work for interprofessional team members to take on discharge tasks and, through a Division of Hospital Medicine internal grant, plans to develop a novel discharge prediction model, structured tools for asynchronous communication and handoff between clinicians and interprofessional team members, and will pilot a delegated discharge model to offload the discharge of clinically stable patients from the primary clinician.

Moving forward, we seek increased support through Caring Wisely to develop a platform to communicate discharge barriers with interprofessional team members and the health system with the goal of reducing length of stay by a further 0.3 days. Our proposal expands the ADP which has already demonstrated LOS reduction and cost savings, with the hope to yield sustained improvement. Specifically:

• Feasible EHR enhancements to existing discharge-focused EHR tools. We have laid the groundwork for interprofessional communication using an order set and discharge checklist to identify discharge tasks and seek to work with Informatics and APeX build support to communicate this at the unit and health system level in a structured and centralized manner. We recognize this will need to synergize with the existing Case Management MDR tool launched 3/12/2025, but hope to use human-centered design principles to optimize how primary hospitalists making the decision to discharge can best interface with the tool in real time, as discharge plans vary throughout the day.
• Improve case management, clinician, and nursing education about discharge-focused tools which can be leveraged in real-time to confirm, document, and overcome discharge barriers.  
• Continue to develop, expand and integrate current ADP deliverables (discharge prediction model, ADP order set, discharge checklist) into a centralized, structured area in the EHR which can be accessed at the unit and health system level and be used by PCMC or individual nursing units to direct resources to ensure timely mobilization after the patient is determined to be medically ready for discharge and discharge orders are placed.

PROPOSED EHR MODIFICATIONS:

We will explore the following modifications which may reduce LOS.

• Expansion and development of current “Discharge Delay” function to identify/flag discharge barriers which already integrates with PCMC workflow
• Continued modification and integration of the standardized inpatient hospital medicine progress note (which now includes listed discharge barriers) and connect this information to the developed centralized EHR enhancements for visibility at the unit and health system level, to escalate and execute discharge tasks.
• Explore similar modification and integration of current Care Management notes as above.
• Reduce redundant areas of interprofessional discharge communication (e.g. Discharge Comments, Case Management Discharge Sticky Note, Patient List columns), instead focusing on the centralized and visible EHR enhancements. 

RETURN ON INVESTMENT:

We anticipate the ADP to produce cost savings through reduction of length of stay in HMS patients. In the latest analyzed data from our current pilot, we found that from October 2023-June 2024, the average length of stay was 7.4 days. This was a 0.7 reduction from the average length of stay of all patients treated by the HMS direct care hospitalists prior to the intervention July 2022-September2023 (8.1 days). We identify a 0.3 day reduction in LOS as a conservative estimate of length of stay reduction by improving interprofessional communication with future support from Caring Wisely. This target is scalable and realistic, even for services with shorter baseline LOS. We identify a 0.7 day reduction in LOS as an optimistic estimate given the data collected.

Collectively, we anticipate direct cost savings to the health system attributed to reduction in HMS length of stay. This will lead to decreased direct variable costs from bed days saved over one year’s time to range from $1,315,242 (0.3 reduction in length of stay for GMS service) to $3,068,898 (0.7 reduction in length of stay for GMS service) as outlined in the attached document. The true financial impact is expected to exceed these figures, as  we expect additional savings from cost of care delivery beyond direct variable bed-day cost   and increase in revenue /contribution margin from backfill of the UCSF Health Parnassus. We have aimed for a smaller impact in part because of anticipated increases in complex patients admitted to Parnassus campus as a result of health system efforts to transfer lower acuity patients to other sites (St. Mary’s Hospital, Mt. Zion Hospital), changes in scheduling practices within HMS, and other system-wide changes which may make it challenging to analyze the individual impact of our project. We believe our project is even more vital in this environment, as the forward flow of patients from all sites will remain a system priority that will be even more challenging for individual clinicians to navigate without care coordination support. To address the challenge of controlling for other concurrent health system efforts, we will continuously adapt our approach and iterate our processes with the guidance of our interprofessional stakeholders, advisors and executive sponsors.

SUSTAINABILITY:

• We aim to intentionally implement interventions that integrate into existing resources/processes and care team members (e.g. Case Management MDR and tee time (afternoon discharge planning), Flow Control Team, HMS direct care clinical assistant, EDD and Discharge Report APeX tools, CARTBoard and enterprise throughput dashboards) to ensure long-term sustainability. The Caring Wisely funding year will be utilized to establish a successful centralized and structured communication enhancement within APeX that can be feasibly adopted by current process owners for hospital discharges and throughput. Once adopted, our intervention will not require ongoing support for maintenance. We anticipate success in this project to lead to adoption of ADP core features and structured communication to scale to other service lines, including our partner sites (St. Mary’s Hospital, Mt. Zion Hospital) which will allow information sharing to enhance discharge workflows across the entire health system.
• We believe our interventions will achieve sustained cost-savings without the need to hire additional care team members. Our goal is to better leverage, connect, and streamline our existing processes to produce faster, safer, and higher quality discharges for patients and care providers alike through improving communication practices, establishing norms, and enhancing APeX as described above.

BUDGET:

• $35,000 – effort for project lead(s)
• $15,000 – reserved for as-needed clinical informatics support (e.g. data analysis, EHR modifications)

PROJECT LEAD(S):

-               Pierre Martin, MD, MEd

-               Andrew Breithaupt, MD

EXECUTIVE SPONSOR(S): 

-               Maggie Waung, MD, PhD

ABSTRACT

Clinicians must distinguish between primary headaches and secondary headaches that require neuroimaging. Limited access to subspecialty headache care leads to misdiagnoses, delays in management, overutilization of neuroimaging, and increased costs, despite clinical practice guidelines and Choose Wisely campaigns.^1–3 Large language models (LLMs), are increasingly used for clinical decision support.⁴ We hypothesize that a chatbot-delivered pre-visit assessment (PVA) combined with an LLM can efficiently collect a comprehensive patient history, accurately diagnose headaches, and provide neuroimaging recommendations similar to an in-person neurologist.  The goal of the intervention is to improve access to headache care and reduce overutilization of neuroimaging, along with associated costs.  For the development and validation phase, participants will be randomized to a person-delivered pre-visit assessment (PVA) or an automated chatbot-delivered PVA.  UCSF Versa, a HIPAA-complaint AI platform, will analyze transcripts to generate a history of present illness, diagnosis and positive or negative recommendation for neuroimaging, for comparison with an in-person neurologist. The chatbot-delivered PVA will later be implemented into clinical workflows by the UCSF General Neurology Clinic and various metrics, including time to diagnosis, neuroimaging utilized and cost of neuroimaging will be calculated for the 6 months before and after implementation. 

TEAM 

-               Project Lead: Pierre Martin, MD, MEd

-               Project Lead: Andrew Breithaupt, MD

-               Lead Researcher: Psalm Pineo-Cavanaugh, BS

-               Lead Developer: Forest Pineo-Cavanaugh, BE

PROBLEM:

Headache disorders affect a wide swath of the population as the third highest cause of disability-adjusted life years worldwide⁵ and often impact people during their peak productive years, extracting a significant financial toll at upwards of $20B annually.^6,7 Accurate and rapid diagnosis of headaches is imperative to treat potentially life-threatening conditions such as subarachnoid hemorrhage, meningitis, or brain tumors. Moreover, early identification and treatment of primary headache disorders (98% of all headaches)⁸ improve outcomes, preventing headaches such as migraine from progressing into debilitating, chronic conditions.⁹ A critical decision point in the accurate diagnosis of headaches is whether brain imaging is needed. If every person with headaches received a MRI Brain, this would place unnecessary strain on the health system¹.  However, not obtaining an MRI in a patient with secondary headaches can be devastating.¹⁰

Two-thirds of the 27 million ED visits are “avoidable”¹¹ and there are 3.5 million “potentially preventable” adult inpatient admissions yearly, accounting for $33.7B in the aggregate¹². Disease management in neurology is particularly expensive because of the complex diagnostic procedures, chronic disease management as well as indirect costs (e.g., lost productivity, disability accommodations).  While neurologist involvement in the ambulatory care setting leads to greater unadjusted allowed third-party payments, it is also associated with increased utilization of both symptom-ameliorating and disease-modifying medications, decreased adverse events, and decreased utilization of both acute and post-acute healthcare resources.¹³  There can be significant interprovider differences in ordering practices and the reasons for this overutilization are multifold, including desire to address the concerns of referring clinicians, appeasement of patients, shortcuts in a busy practice, cognitive bias and defensive medicine.^14,15  Overutilization burdens the healthcare system, can impact insurance coverage and in turn reduces access to care for patients with more critical neurological conditions.  Reduced access to care invariably leads to a worsened prognosis and increased acute care utilization (e.g., ED visits and inpatient admissions).

Standardization and clinical practice guidelines help to narrow practice variation and can reduce cost without a reduction in clinical outcomes.¹⁶ The American Headache Society and American College of Radiology emphasize that neuroimaging is not necessary for uncomplicated headaches that meet ICHD-3 criteria for migraine, do not have “red flag” symptoms/signs and maintain a normal neurological examination.¹⁴  For example, most brain tumor patients present with multiple symptoms/signs, while only 12% present with isolated headache and 3% are incidental.¹⁷ Despite clinical practice guidelines and Choose Wisely healthcare campaigns, 12 – 16% of patient with primary headaches undergo MRI neuroimaging^1–3 as overutilization in this setting contributes to $1 – 3B per year in avoidable imaging costs.¹⁴  Moreover, overutilization of neuroimaging can lead to false positives, resultant patient anxiety and unnecessary follow-up diagnostics, interventions and consultations with their own associated risks. 

Headaches are one of the more common neurological conditions managed in the UCSF General Neurology Clinic.  During 2024, the UCSF General Neurology Clinic received between 1000 - 1400 new patient referrals per month and a significant proportion of those referrals were related to headache management, between 100 - 280 referrals per month.  And the catchment area for UCSF General Neurology Clinic is increasing in size, year by year.  Hundreds of new headache patients are seen per month between UCSF General Neurology and UCSF Headache clinics, some presenting with or without recent neuroimaging.   Moreover, there are growing concerns that changes in both federal and state level healthcare policies will lead to significant reductions in insurance coverage, funding cuts to Medicaid, and changes in reimbursement rates, which will all further exacerbate the problem of reduced access to neurological care.  This will be particularly true for underserved regions and vulnerable patient populations.  Innovative solutions to improve access to neurological care and reduce healthcare costs are imperative.

TARGET:

Goal: We aim to develop, validate and safely implement a chatbot-delivered PVA combined with a LLM to 1) improve patient access to headache care and 2) reduce overutilization of neuroimaging for headache management.

 Expected quantitative benefits:

-        Decrease in time to diagnosis

-        Decrease in time to diagnostic testing

-        Decrease in unnecessary diagnostic tests (i.e., neuroimaging)

-        Reduction in healthcare expenses associated with the decrease in unnecessary diagnostic tests (i.e., neuroimaging)

-        Reduction in acute care utilization

Expected qualitative benefits:

-        Improved and more efficient clinical workflow for patients

GAPS:

While neurologists are well equipped to evaluate and diagnose headache disorders, primary and acute care providers are usually the first line of care for patients with headache^9,18. Quality and depth of training for these providers on the management of headache disorders is highly variable.^19,20 And providers maintain variable awareness of clinical practice guidelines and Choosing Wisely Campaigns. Furthermore, the global shortage of neurologists results in limited access to subspecialty headache care, often leading to misdiagnosis and delays in management, which are further compounded in low-resource and rural settings.²¹  There has been increasing research into the potential of large language models, a subset of generative AI, to help providers (neurologists and non-neurologists) more accurately and efficiently triage, diagnose and manage headache patients.²²

INTERVENTION:
Generative AI with LLMs like OpenAI’s generative pre-trained transformers (ChatGPT-3, ChatGPT-4) is being increasingly studied and implemented throughout medicine, from virtual assistants to clinical decision support.^23–26 Despite the promise of utilizing LLMs for medical purposes, the data on the diagnostic accuracy of generative AI compared to physicians is mixed.^27–31 With respect to LLMs in particular, ChatGPT-3 has been used to develop lists of five differential diagnoses based on ten mock clinical vignettes and contained the correct diagnosis upwards of 80% of the time.³² LLMs may outperform physicians in terms of diagnosis and clinical reasoning in certain circumstances, but may actually hamper physician accuracy when used without appropriate training.³³ That being said, these systems will need to be investigated further given continued concerns about accuracy, reliability and bias in clinical settings.³⁴ LLMs can incorporate clinical practice guidelines³⁵ and can be integrated into clinical workflows for clinical decision support such as structured symptom assessments for patient triage, risk stratification and initial recommendations.  As a result, there is ongoing research into how to appropriately implement these systems,^36,37 including for headache diagnosis and management. Headache classification is a common application of generative AI with PVAs serving as a source of rich phenotypic data.³⁸  Technological advances such as enhanced LLMs that incorporate clinical practice guidelines have the opportunity to increase clinical efficiency, improve access to neurological care and promote diagnostic stewardship, all the while decreasing overutilization of resources and driving down costs.

 Approach:

Hypothesis: We hypothesize that a chatbot-delivered PVA combined with an LLM can efficiently collect a comprehensive patient history, accurately diagnose headache syndromes, and provide imaging recommendations similar to an in-person neurologist.

Aim 1: Evaluate the diagnostic accuracy and imaging recommendations of an LLM for primary and secondary headaches. We hypothesize that a fine-tuned LLM using the results of a chatbot-delivered PVA will diagnose headache disorders and make imaging recommendations with a concordance of at least 0.8 with a blinded in-person neurologist. 

Aim 2: Evaluate clinical efficiency, resource utilization and cost reductions associated with implementation of a chatbot-delivered PVA combined with an LLM for headache management.  After implementation for new headache patient referrals, we will calculate the time to diagnosis (by fine-tuned LLM and then in-person neurologist) as well as record if the LLM recommended neuroimaging, if patients underwent neuroimaging and the costs associated with neuroimaging (based on EHR logs and administrative billing records).  We will compare the aforementioned metrics during the 6 months before and after implementation of the chatbot-delivered PVA and LLM into clinical workflows.

Methods: Development and Validation

160 participants will be recruited to achieve a 95% CI with a sensitivity of 0.80 and a margin of error of ±0.062. and include adult English-speaking patients scheduled to be seen in the UCSF General Neurology Clinic for headache management within 6 months of enrollment. This study will be conducted in collaboration with the neurology and computer science departments at Emory University, who will provide chatbot and secure server support.

Participants will be randomized to either a 1) person-delivered PVA administered by study staff via Zoom or 2) an automated chatbot-delivered PVA. A chatbot for the PVA was developed and will be deployed via Emory’s Amazon Web Services (AWS; cloud computing platform for storage, computing, and databases). Participants will undergo 1:1 block randomization between the 2 arms. 

Audio recordings of the PVAs will be transcribed to text via OpenAI’s Whisper (automated speech recognition system). Recordings and transcripts will be stored on the UCSF Research Analysis Environment (data hosting and collaboration tool). Whisper- and chatbot-generated transcripts of the PVA will be entered into UCSF Versa, a HIPAA-complaint AI platform that allows users to interact with ChatGPT-3.5 and ChatGPT-4.0. UCSF Versa will be prompted to analyze the transcripts, generating both a diagnosis based on International Classification of Headache Disorders 3 criteria⁴¹ and a positive or negative recommendation for neuroimaging.

All patients will receive a detailed clinical history and neurological physical examination, which will be documented by the blinded in-person neurologist. Blinded study staff will review the neurologist’s clinic note for each patient and enter the diagnosis and imaging recommendations into REDCap.

This proposal has already been approved by the UCSF IRB (23-40675). Development of a REDCap Database and person-delivered PVA questionnaire has been completed.  Participant recruitment has started; 10 have completed PVAs.

Methods: Implementation and Evaluation

Subsequently, the chatbot-delivered PVA will be implemented into the clinical workflow for new headache patient management in the UCSF General Neurology Clinic.  New headache patient referrals will be randomized to either chatbot-delivered PVA and LLM evaluation vs standard of care.  Results of the chatbot-delivered PVA and LLM will be sent to primary care physicians for headache management. The time to diagnosis (via LLM or neurologist), neuroimaging recommended/obtained and cost of the associated neuroimaging obtained will be calculated for the 6 months before and after clinical implementation.  And the results will be compared between the two cohorts.

UCSF General Neurology Clinic:

Provider Characteristics: There are 9 board certified neurologists and 1 physician assistant employed.

Staff Characteristics: There are multiple patient coordinators, nurses and other staff.

Patient Characteristics: Adult patients 18+ years old

Potential Barriers to Implementation:

LLMs are being increasing used in medicine for various purpose from administrative tasks to clinical decision support.⁴  That being said there remain concerns related to the accuracy, reliability, and bias associated with LLMs as up as until recently they maintained limited clinical reasoning and produced hallucinations.³⁴ This LLM will be enhanced with the ICHD3 criteria for headache diagnosis in order to improve diagnostic accuracy.  And the initial phase of the project involves validation of the LLM’s diagnostic performance.  Moreover, effective engagement with these systems by patients necessitates a level of digital health literacy, which could be a potential source of equity bias.  Patients may benefit from educational resources to facilitate engagement with the chatbot-delivered PVA.  There is a need for standardized validation procedures and actionable guidelines for healthcare organizations as well as providers to ensure responsible implementation of LLM in the clinical setting.³⁴ 

We anticipate that the risks to the patient are minimal.  Some patients have reservations about the accuracy, lack of empathy, and potential for privacy breeches associated with AI-integrated technologies.⁴² Patient data is de-identified and we rigorously adhere to IRB protocols and privacy standards to ensure that patient confidentiality is fully maintained.  Moreover, while the goal is to reduce the overutilization of neuroimaging for uncomplicated headaches, a proportion of patients may receive a recommendation to obtain neuroimaging, which uncovers an incidental finding and leads to subsequent unnecessary testing and avoidable patient anxiety. 

PROPOSED EHR MODIFICATIONS:  

After the initial validation and implementation of the chatbot-delivered PVA and LLM, it could be incorporated into the electronic health record and require the following features 1) inclusion of MyChart Link for patients to access chatbot-delivered PVA and 2) an automated process to capture the results of the chatbot-delivered PVA with LLM and send results to referring providers and future neurologist. 

RETURN ON INVESTMENT (ROI) 

MRIs alone account for 51% of total healthcare expenditures in outpatient neurology.⁴¹  And the average cost of an MRI ranges from $1,600 – 8,400⁴² depending on extent of structures evaluated, insurance coverage, healthcare facility location, healthcare facility type, and need for contrast media.  One Choosing Wisely campaign assessing the impact of the campaign on the use of brain MRI in preterm infants was associated with a significant decrease in non-indicated MRIs with expenditures decreasing from $1.3M in 2006 to $260,000 in 2016.⁴³  While another study revealed that a Choosing Wisely campaign for headaches was associated with a significant reduction in imaging for uncomplicated headaches from 10.8% to 6.9% in a 3-year period, which led to significant savings.⁴⁴  Over the long-term period, indirect cost savings will include reductions associated with a decrease in acute care utilization (e.g., ED visits, inpatient admissions), decrease in unnecessary diagnostics following up incidental findings as well as improvements in lost productivity of patients.  

SUSTAINABILITY 

The Technology Chief for UCSF’s General Neurology Division will be responsible for ongoing enhancements to the system.  The Division Chief for UCSF’s General Neurology Division will be the executive sponsor for oversight and budgeting operational resources.

BUDGET  

Faculty Protected Salary Time for Project Implementation: $38,000.00

Research Coordinator Stipend(s): $12,000.00

• PROJECT LEAD(S): Lan Vu, MD, MAS; Doruk Ozgediz, MD, MSc
• EXECUTIVE SPONSOR(S): Atsuko Baba, MD; Hanmin Lee, MD
• ABSTRACT - One paragraph summary of your proposed initiative – Limit 1500 characters (with spaces)

There is growing literature on the importance of social drivers of health (SDoH) on surgical quality outcomes in the pediatric population.  Patient navigator programs have been shown to address and minimize the impact of SDoH at multiple levels.  In addition, these risk factors have been shown to be associated with surgery same day cancellations, which impacts access to equitable health care for children.  We propose to develop community-based patient navigator program as an intervention to provide resources for high-risk patients, identified by individual and neighborhood-level SDoH screening in the Pre-Surgery clinic at Children’s Hospital in San Francisco and Oakland.

TEAM - 
Phillip Herrera (ZSFG Health Advocate Program coordinator): Mentor/Consultant
The nurse practitioners who will performing the individual-level SDoH screening (Amanda Parker, NP, Anne Hagbom, NP, Mellany Aquino, NP, Bianca Juarez, NP, Megan Drombroski, NP, Jessica Pascual, NP)
Lauren Puplampu and Alondra Aguilar (currently students in the UCSF-UC Berkeley Joint Medical Program, in the progress of training to become patient navigators in the ZSFG Health Advocate Program)

• PROBLEM – Surgical quality outcomes is strongly tied to social drivers of health (SDoH) in the pediatric population.  Recent literature highlights the impact of race and ethnicity on postoperative mortality in healthy children. Compared with being white, African-American children had 3.43 times the odds of dying within 30 days after surgery, 18% relative greater odds of developing postoperative complications, and 7% relative higher odds of developing serious adverse events. (Nafiu et al, JAMA Surg, 2020).  Looking specifically at our institution’s pediatric cohort, 12% of the NSQIP-P population had high Social Vulnerability Index (SVI) and this was associated with postoperative complications. (Yap et al, Am J Surg, 2023).  Currently, there is variability in SDoH assessment of the surgical population and limited resources to address these risks when they are identified (Sokol et al, Pediatrics, 2019).  Patient-navigator programs have led to improved processes of care, patient experience, clinical outcomes and costs for children with chronic conditions (McBrien et al, PLoS One 2018). Surgery same day cancellations is an important metric to assess the success of the Pre-Surgery clinic at UCSF.  There has been a recent uptrend in the reasons for same day cancellations of late arrivals and no shows, which may be secondary to modifiable SDoH risk factors.  The mechanism to screen for SDoH (financial resource strain, food insecurity, housing stability, and transportation needs) currently exist in the UCSF Epic system.  However, there is limited social worker resource (0.25 FTE) in the Pediatric Pre-surgery clinic to address these needs when identified. 
• TARGET - Children scheduled for surgery at the Benioff Children’s Hospitals in San Francisco and Oakland. 

Outcome metrics:

1. Distribution of individual-level and neighborhood-level SDoH in our current surgical patient population
2. Successful contact with families by the patient navigator
3. Quality metrics: Surgery same day cancellations rates and ED visits within 30 days of procedure before and after implementation of patient navigator program
4. Comparing individual-level SDoH with neighborhood level-level SDoH (SVI and COI) and their impact in on the surgical outcomes in the NSQIP-P database.
5. Results of patient/family satisfaction survey after enrollment in the program

 The expected benefits include decline in of the number of same day cancellations based on modifiable reasons (ie no shows and late arrivals), improved patient experience and patient/families’ satisfaction in the immediate study period. In the long term, we expect improvement in surgical quality outcomes as assessed through the NSQIP-P database which may allow us to determine the role/impact of individual versus neighborhood-level SDoH. 

• GAPS - Why does the problem exist?  Describe system issues; technological gaps; educational gaps

The mechanism to screen for SDoH (financial resource strain, food insecurity, housing stability, and transportation needs) currently exist in the UCSF Epic system.  However, there is limited social worker resource in the Pediatric Pre-surgery clinic to address these needs when identified. In addition, social worker does not address the barriers at the community level which would be the focus of the patient navigator program.   

• INTERVENTION 

Study Design:
Phase 1: Patient Navigator training program (already started on January 2025)

• 6 to 12- month commitment to the Health Advocate program at ZSFG
• Needs assessment: Mapping the geographic distribution of the surgical patients, identifying the high yield counties, and creating county-based community resource algorithms addressing the key SDoH.

Phase 2: Intervention
1. SDoH screening at Prepare clinic appointment:

• 8 screening questions on Epic: financial resource strain, housing stability, food insecurity, transportation needs, utilities to assess individual-level SDoH
• Patients/families identified as high risk for any of the categories will be given access to resources in local community (https://www.findhelp.org/) and asked to participate in Patient Navigator program.
• SDoH risk assessment entered into NSQIP-P database by SCR (surgical clinical reviewer)

2. Intervention Phase:

• 1^st call: provide local community resources before procedure date
• 2^nd call: follow-up one week after procedure
• 3^rd call: follow-up one month after procedure
• 4^th call: follow-up two months after procedure (plus administration of satisfaction survey)

Study Duration: one year

Patient Population:

All children who will be evaluated at Pediatric Prepare clinic before scheduled procedure at BCH SF, plan to expand to BCH-Oakland after pilot period of 3 months at BCH-SF

Sample size: total 7,000 surgical procedures (1500 anesthesia nonsurgical procedures), about 50% of cases are scheduled outpatient cases

Current proportion of cohort considered high risk for SDoH: estimated 12% (based in NSQIP-P data)

Estimated N=420 patients (high risk) in one year

• PROPOSED EHR MODIFICATIONS Individual-level SDoH screening questions already exist as part of the storyboard on Epic. We are requesting the addition of neighborhood-level SDoH assessment be included into Epic by geocoding the home addresses and converting into SVI and COI percentile (1-100, higher percentile notates higher level of social vulnerability).  The algorithm has already been developed (Yap et al, J Am Surg, 2023).

• RETURN ON INVESTMENT (ROI) Estimated direct cost savings to the health care system cannot easily be calculated. However, decrease in surgery same day cancellations will allow for better OR block time utilization, leading to improved revenue.  Decrease postoperative complications would impact health care costs as documented in the NSQIP-P database (include postop ED visits, hospital readmissions, and hospital length of stay). 

• SUSTAINABILITY -If successful, the patient navigator program will be sustained by hiring a cross-bay program coordinator who will work in synergy with the social workers in the Pre-Surgery Clinic at Mission Bay and Oakland.  Dr. Lan Vu, as the current Medical Director of Surgical Quality and Safety at Mission Bay will take on the additional responsibility of supervising this program. The role and responsibilities of that program coordinator are listed below.  Medical Director of Pediatric Perioperative Services (Dr. Atsuko Baba) and Surgeon in Chief for the UCSF Benioff Children’s Hospital in San Francisco (Dr. Hanmin Lee) are both executive sponsors for this proposal and are committed to providing operational resources and funding after the project year.

• BUDGET - Line-item budget up to $50,000 - Briefly identify key areas of the project that will require funding, e.g., salaries, software, printing, etc
  
  Stipend for Health Advocate Program Coordinator as consultant          $30,000    
  0.1FTE Medical Director                                                                         $10-20,000

See below for shared responsibilities of Program coordinator and Medical Director

Patient Navigator Program Development: Leverage experience from the Health Advocates program to assist with the implementation of a patient resource navigator program tailored to the Pre-Surgery Clinic's needs.

Workflow and Algorithm Creation: Develop and optimize workflows and algorithms to ensure efficient SDoH screening, resource referrals, and follow-up, drawing on proven methodologies from Health Advocates program.

Community Resource Collaboration: Provide strategic input into the identification and integration of county-specific resources, ensuring navigators are equipped with actionable tools to address diverse patient needs across California.

Data-Driven Quality Improvement: Collaborate with identifying appropriate methods for collecting and analyzing program data, such as SDoH impact metrics and patient satisfaction, to demonstrate program effectiveness.

Strategic Stakeholder Engagement: Collaborate with clinical teams, community organizations, and the study leadership to align program objectives and foster partnerships that enhance resource accessibility and patient outcomes

• Center for Health Equity in Surgery and Anesthesia (CHESA) and the Division of Pediatric Surgery have expressed commitment to providing additional funding if needed to support this program.