Catalyzing System Change: 100 Quality Improvement Projects in 1000 Days.

BACKGROUND: Health system change requires quality improvement (QI) infrastructure that supports frontline staff implementing sustainable innovations. We created an 8-week rapid-cycle QI training program, Stanford Primary Care-Project Engagement Platform (PC-PEP), open to patient-facing primary care clinicians and staff. OBJECTIVE: Examine the feasibility and outcomes of a scalable QI program for busy practicing providers and staff in an academic medical center. DESIGN: Program evaluation. PARTICIPANTS: A total of 172 PCPH team members: providers (n = 55), staff (n = 99), and medical learners (n = 18) in the Stanford Division of Primary Care and Population Health (PCPH) clinics, 2018-2021. MAIN MEASURES: We categorized projects by the Institute for Healthcare Improvement's (IHI) Quintuple Aim (QA): better health, better patient experience, lower cost of care, better care team experience, and improved equity/inclusion. We assessed project progress with a modified version of The Ottawa Hospital Innovation Framework: step 1 (identified root causes), step 2 (designed/tested interventions), step 3 (assessed project outcome), step 4 (met project goal with target group), step 5A (intervention(s) spread within clinic), step 5B (intervention(s) spread to different setting). Participants rated post-participation QI self-efficacy. KEY RESULTS: Within 1000 days, 172 unique participants completed 104 PC-PEP projects. Most projects aimed to improve patient health (55%) or care team experience (23%). Among projects, 9% reached step 1, 8% step 2, 16% step 3, 26% step 4, 21% step 5A, and 20% step 5B. Learner involvement increased likelihood of scholarly products (47% vs 10%). Forty-six of 47 (98%) survey respondents reported improved QI self-efficacy. Medical assistants, more so than physicians, reported feeling acknowledged by the health system for their QI efforts (100% vs 61%). CONCLUSIONS: With appropriate QI infrastructure, scalable QI training models like Stanford PC-PEP can empower frontline workers to create meaningful changes across the IHI QA.

Targeted Electronic Patient Portal Messaging Increases Hepatitis C Virus Screening in Primary Care: a Randomized Study.

IMPORTANCE: Electronic health record (EHR) tools such as direct-to-patient messaging and automated lab orders are effective at improving uptake of preventive health measures. It is unknown if patient engagement in primary care impacts efficacy of such messaging. OBJECTIVE: To determine whether more engaged patients, defined as those who have an upcoming visit scheduled, are more likely to respond to a direct-to-patient message with an automated lab order for hepatitis C virus (HCV) screening. DESIGN: Randomized trial PARTICIPANTS: One thousand six hundred randomly selected Stanford Primary Care patients, 800 with an upcoming visit within 6 months and 800 without, born between 1945 and 1965 who were due for HCV screening. Each group was randomly divided into cohorts of 400 subjects each. Subjects were followed for 1 year. INTERVENTION: One 400 subject cohort in each group received a direct-to-patient message through the EHR portal with HCV antibody lab order. MAIN OUTCOME AND MEASURE: The EHR was queried on a monthly basis for 6 months after the intervention to monitor which subjects completed HCV screening. For any subjects screened positive for HCV, follow-up through the cascade of HCV care was monitored, and if needed, scheduled by the study team. KEY RESULTS: Of 1600 subjects, 538 (34%) completed HCV screening. In the stratum without an upcoming appointment, 18% in the control group completed screening compared to 26% in intervention group (p<0.01). Similarly, in the stratum with an upcoming appointment, 34% in the control group completed screening compared to 58% in the intervention group (p<0.01). CONCLUSION: Direct-to-patient messaging coupled with automated lab orders improved HCV screening rates compared to standard of care, particularly in more engaged patients. Including this intervention in primary care can maximize screening with each visit, which is particularly valuable in times when physical throughput in the healthcare system may be low.

Qualitative Assessment of Rapid System Transformation to Primary Care Video Visits at an Academic Medical Center.

BACKGROUND: The coronavirus disease 2019 pandemic spurred health systems across the world to quickly shift from in-person visits to safer video visits. OBJECTIVE: To seek stakeholder perspectives on video visits' acceptability and effect 3 weeks after near-total transition to video visits. DESIGN: Semistructured qualitative interviews. SETTING: 6 Stanford general primary care and express care clinics at 6 northern California sites, with 81 providers, 123 staff, and 97 614 patient visits in 2019. PARTICIPANTS: 53 program participants (overlapping roles as medical providers [n = 20], medical assistants [n = 16], nurses [n = 4], technologists [n = 4], and administrators [n = 13]) were interviewed about video visit transition and challenges. INTERVENTION: In 3 weeks, express care and primary care video visits increased from less than 10% to greater than 80% and from less than 10% to greater than 75%, respectively. New video visit providers received video visit training and care quality feedback. New system workflows were created to accommodate the new visit method. MEASUREMENTS: 9 faculty, trained in qualitative research methods, conducted 53 stakeholder interviews in 4 days using purposeful (administrators and technologists) and convenience (medical assistant, nurses, and providers) sampling. A rapid qualitative analytic approach for thematic analysis was used. RESULTS: The analysis revealed 12 themes, including Pandemic as Catalyst; Joy in Medicine; Safety in Medicine; Slipping Through the Cracks; My Role, Redefined; and The New Normal. Themes were analyzed using the RE-AIM (reach, effectiveness, adoption, implementation, and maintenance) framework to identify critical issues for continued program utilization. LIMITATIONS: Evaluation was done immediately after deployment. Although viewpoints may have evolved later, immediate evaluation allowed for prompt program changes and identified broader issues to address for program sustainability. CONCLUSION: After pandemic-related systems transformation at Stanford, critical issues to sustain video visit long-term viability were identified. Specifically, technology ease of use must improve and support multiparty videoconferencing. Providers should be able to care for their patients, regardless of geography. Providers need decision-making support with virtual examination training and home-based patient diagnostics. Finally, ongoing video visit reimbursement should be commensurate with value to the patients' health and well-being. PRIMARY FUNDING SOURCE: Stanford Department of Medicine and Stanford Health Care.

Differences and Trends in DNR Among California Inpatients With Heart Failure.

BACKGROUND: Do-not-resuscitate (DNR) orders reflect an important means of respecting patient autonomy while minimizing the risk of nonbeneficial interventions. We sought to clarify trends and differences in rates of DNR orders for patients hospitalized with heart failure. METHODS: We used statewide data from California's Healthcare Cost and Utilization dataset (2007-2010) to determine trends in DNR orders within 24 hours of admission for patients with a primary discharge diagnosis of heart failure. RESULTS: Among 347,541 hospitalizations for heart failure, the rate of DNR order within 24 hours increased from 10.4% in 2007 to 11.3% in 2010 (P < .0001). After adjustment, DNR status correlated with older age, female gender, white race, frequent comorbidities (Charlson Score), and residence in higher income area (P < .0001). DNR use was more likely in hospitals with public or nonprofit financing or medical school affiliation, but not being a member of the Council on Teaching Hospitals (all P < .001). CONCLUSION: DNR order use among inpatients with heart failure is low but increasing slowly and varies by patient demographics and hospital characteristics.

How Many Lives Will You Save? A Mixed Methods Evaluation of a Novel, Online Game for Patient Safety and Quality Improvement Education.

Medical trainees have limited knowledge of quality improvement and patient safety concepts. The authors developed a free quality improvement/patient safety educational game entitled Safety Quest (SQ). However, 1803 undergraduate medical trainees, graduate medical trainees, and continuing medical education learners globally completed at least 1 level of SQ. Pre- and post-SQ knowledge and satisfaction were assessed among continuing medical education learners. Thematic analysis of feedback given by trainees was conducted. Among graduate medical trainees, SQ outranked other learning modalities. Three content areas emerged from feedback: engagement, ease of use, and effectiveness; 87% of comments addressing engagement were positive. After completing SQ, 98.6% of learners passed the post-test, versus 59.2% for the pretest ( P < 0.0001). Ninety-three percent of learners agreed that SQ was engaging and interactive, and 92% believed it contributed to their professional growth. With an increased need for educational curricula to be delivered virtually, gamification emerges as a unique strategy that learners praise as engaging and effective.

Artificial Intelligence Improves Patient Follow-Up in a Diabetic Retinopathy Screening Program.

Purpose: We examine the rate of and reasons for follow-up in an Artificial Intelligence (AI)-based workflow for diabetic retinopathy (DR) screening relative to two human-based workflows. Patients and Methods: A DR screening program initiated September 2019 between one institution and its affiliated primary care and endocrinology clinics screened 2243 adult patients with type 1 or 2 diabetes without a diagnosis of DR in the previous year in the San Francisco Bay Area. For patients who screened positive for more-than-mild-DR (MTMDR), rates of follow-up were calculated under a store-and-forward human-based DR workflow ("Human Workflow"), an AI-based workflow involving IDx-DR ("AI Workflow"), and a two-step hybrid workflow ("AI-Human Hybrid Workflow"). The AI Workflow provided results within 48 hours, whereas the other workflows took up to 7 days. Patients were surveyed by phone about follow-up decisions. Results: Under the AI Workflow, 279 patients screened positive for MTMDR. Of these, 69.2% followed up with an ophthalmologist within 90 days. Altogether 70.5% (N=48) of patients who followed up chose their location based on primary care referral. Among the subset of patients that were seen in person at the university eye institute under the Human Workflow and AI-Human Hybrid Workflow, 12.0% (N=14/117) and 11.7% (N=12/103) of patients with a referrable screening result followed up compared to 35.5% of patients under the AI Workflow (N=99/279; χ2df=2 = 36.70, p < 0.00000001). Conclusion: Ophthalmology follow-up after a positive DR screening result is approximately three-fold higher under the AI Workflow than either the Human Workflow or AI-Human Hybrid Workflow. Improved follow-up behavior may be due to the decreased time to screening result.

AI-Human Hybrid Workflow Enhances Teleophthalmology for the Detection of Diabetic Retinopathy.

Objective: Detection of diabetic retinopathy (DR) outside of specialized eye care settings is an important means of access to vision-preserving health maintenance. Remote interpretation of fundus photographs acquired in a primary care or other nonophthalmic setting in a store-and-forward manner is a predominant paradigm of teleophthalmology screening programs. Artificial intelligence (AI)-based image interpretation offers an alternative means of DR detection. IDx-DR (Digital Diagnostics Inc) is a Food and Drug Administration-authorized autonomous testing device for DR. We evaluated the diagnostic performance of IDx-DR compared with human-based teleophthalmology over 2 and a half years. Additionally, we evaluated an AI-human hybrid workflow that combines AI-system evaluation with human expert-based assessment for referable cases. Design: Prospective cohort study and retrospective analysis. Participants: Diabetic patients ≥ 18 years old without a prior DR diagnosis or DR examination in the past year presenting for routine DR screening in a primary care clinic. Methods: Macula-centered and optic nerve-centered fundus photographs were evaluated by an AI algorithm followed by consensus-based overreading by retina specialists at the Stanford Ophthalmic Reading Center. Detection of more-than-mild diabetic retinopathy (MTMDR) was compared with in-person examination by a retina specialist. Main Outcome Measures: Sensitivity, specificity, accuracy, positive predictive value, and gradability achieved by the AI algorithm and retina specialists. Results: The AI algorithm had higher sensitivity (95.5% sensitivity; 95% confidence interval [CI], 86.7%-100%) but lower specificity (60.3% specificity; 95% CI, 47.7%-72.9%) for detection of MTMDR compared with remote image interpretation by retina specialists (69.5% sensitivity; 95% CI, 50.7%-88.3%; 96.9% specificity; 95% CI, 93.5%-100%). Gradability of encounters was also lower for the AI algorithm (62.5%) compared with retina specialists (93.1%). A 2-step AI-human hybrid workflow in which the AI algorithm initially rendered an assessment followed by overread by a retina specialist of MTMDR-positive encounters resulted in a sensitivity of 95.5% (95% CI, 86.7%-100%) and a specificity of 98.2% (95% CI, 94.6%-100%). Similarly, a 2-step overread by retina specialists of AI-ungradable encounters improved gradability from 63.5% to 95.6% of encounters. Conclusions: Implementation of an AI-human hybrid teleophthalmology workflow may both decrease reliance on human specialist effort and improve diagnostic accuracy. Financial Disclosures: Proprietary or commercial disclosure may be found after the references.

Transforming Interprofessional Roles During Virtual Health Care: The Evolving Role of the Medical Assistant, in Relationship to National Health Profession Competency Standards.

INTRODUCTION: Medical assistants (MAs) were once limited to obtaining vital signs and office work. Now, MAs are foundational to team-based care, interacting with patients, systems, and teams in many ways. The transition to Virtual Health during the COVID-19 pandemic resulted in a further rapid and unique shift of MA roles and responsibilities. We sought to understand the impact of this shift and to place their new roles in the context of national professional competency standards. METHODS: In this qualitative, grounded theory study we conducted semi-structured interviews with 24 MAs at 10 primary care sites at a major academic medical center on their experiences during the shift from in-person to virtual care. MAs were selected by convenience sample. Coding was done in Dedoose version 8.335. Consensus-based inductive and deductive approaches were used for interview analysis. Identified MA roles were compared to national MA, Institute of Medicine, physician, and nursing professional competency domains. RESULTS: Three main themes emerged: Role Apprehension, Role Expansion, and Adaptability/Professionalism. Nine key roles emerged in the context of virtual visits: direct patient care (pre-visit and physical care), panel management, health systems ambassador, care coordination, patient flow coordination, scribing, quality improvement, and technology support. While some prior MA roles were limited by the virtual care shift, the majority translated directly or expanded in virtual care. Identified roles aligned better with Institute of Medicine, physician, and nursing professional competencies, than current national MA curricula. CONCLUSIONS: The transition to Virtual Health decreased MA's direct clinical work and expanded other roles within interprofessional care, notably quality improvement and technology support. Comparison of the current MA roles with national training program competencies identified new leadership and teamwork competencies which could be expanded during MA training to better support MA roles on inter-professional teams.

Impaired visual fixation at the age of 2 years in children born before the twenty-eighth week of gestation. Antecedents and correlates in the multicenter ELGAN study.

BACKGROUND: Very little is known about the prevalence, antecedents, and correlates of impaired visual fixation in former very preterm newborns. METHODS: In the multicenter ELGAN study sample of 1057 infants born before the twenty-eighth week of gestation who had a developmental assessment at 2 years corrected age, we identified 73 who were unable to follow an object across the midline. We compared them to the 984 infants who could follow an object across the midline. RESULTS: In this sample of very preterm newborns, those who had impaired visual fixation were much more likely than those without impaired visual fixation to have been born after the shortest of gestations (odds ratio, 3.2; 99% confidence interval, 1.4-7.5) and exposed to maternal aspirin (odds ratio, 5.2; 99% confidence interval, 2.2-12). They were also more likely than their peers to have had prethreshold retinopathy of prematurity (odds ratio, 4.1; 99% confidence interval, 1.8-9.0). At age 2 years, the children with impaired fixation were more likely than others to be unable to walk (even with assistance) (odds ratio, 7.5; 99% confidence interval, 2.2-26) and have a Mental Development Index more than three standard deviations below the mean of a normative sample (odds ratio, 3.6; 99% confidence interval, 1.4-8.2). CONCLUSION: Risk factors for brain and retinal damages, such as very low gestational age, appear to be risk factors for impaired visual fixation. This inference is further supported by the co-occurrence at age 2 years of impaired visual fixation, inability to walk, and a very low Mental Development Index.

Early treatment suppresses the development of spike-wave epilepsy in a rat model.

PURPOSE: Current treatments for epilepsy may control seizures, but have no known effects on the underlying disease. We sought to determine whether early treatment in a model of genetic epilepsy would reduce the severity of the epilepsy phenotype in adulthood. METHODS: We used Wistar albino Glaxo rats of Rijswijk (WAG/Rij) rats, an established model of human absence epilepsy. Oral ethosuximide was given from age p21 to 5 months, covering the usual period in which seizures develop in this model (age approximately 3 months). Two experiments were performed: (1) cortical expression of ion channels Nav1.1, Nav1.6, and HCN1 (previously shown to be dysregulated in WAG/Rij) measured by immunocytochemistry in adult treated rats; and (2) electroencephalogram (EEG) recordings to measure seizure severity at serial time points after stopping the treatment. RESULTS: Early treatment with ethosuximide blocked changes in the expression of ion channels Nav1.1, Nav1.6, and HCN1 normally associated with epilepsy in this model. In addition, the treatment led to a persistent suppression of seizures, even after therapy was discontinued. Thus, animals treated with ethosuximide from age p21 to 5 months still had a marked suppression of seizures at age 8 months. DISCUSSION: These findings suggest that early treatment during development may provide a new strategy for preventing epilepsy in susceptible individuals. If confirmed with other drugs and epilepsy paradigms, the availability of a model in which epileptogenesis can be controlled has important implications both for future basic studies, and human therapeutic trials.