Building an Ambulatory Patient Safety Learning Laboratory for Diverse Populations (ASCENT)

Principal Investigator: Urmimala Sarkar, M.D., M.P.H., University of California-San Francisco, San Francisco, CA
AHRQ Grant No.: HS023558
Project Period: 09/30/14-09/29/20
Description: The overall goal of this project was to examine the epidemiology of patient safety in ambulatory care settings that care for diverse, low-income populations in the San Francisco Heath Network (SFHN).

The project aims were to:

• Create a transdisciplinary patient safety learning laboratory composed of stakeholders and experts in patient safety, reliability science, design thinking, and operational leadership to collaborate on creative and effective solutions.
• Design and iterate technical and workflow solutions for high-priority ambulatory safety issues in a publicly funded, safety-net healthcare system caring for diverse, vulnerable patients. Specifically, ASCENT addressed (a) test results management, (b) outpatient monitoring for high-risk conditions, and (c) enhanced medication comprehension to reduce adverse drug events.
• Implement and evaluate solutions using implementation sciences methodology.
• Scale up effective solutions across the health system and disseminate them among safety-net health systems.

The ASCENT Lab developed, piloted, and implemented a needs-driven technical and culture-based solution for subcritical test results, management of high-risk conditions and treatments, and patient-centered medication language with rich involvement from frontline clinicians and leadership in the health system.¹

The ASCENT Lab's innovations included creating test results and population management software that allowed healthcare professionals to actively track subcritical test results (e.g., pulmonary nodules) and monitor high-risk populations or treatments (e.g., patients with cancer or patients receiving anticoagulation therapy).^2-5

Examples of such innovations:

• An electronic registry for urology clinic staff to monitor men on active surveillance for prostate cancer risk.⁴ Currently being evaluated, use of the registry will assess the efficacy and feasibility of health information technology at a safety-net hospital to ensure patients receive guideline-recommended care.
• A health information technology platform that monitors patients with head and neck cancer to improve timely and successful completion of guideline-based care processes.³
• An electronic dashboard (integrated into a preexisting electronic health record) and standardized workflow to track patients' laboratory results, identify patients requiring followup, and facilitate use of a validated nomogram for dose adjustment.⁶

The ASCENT Lab also implemented and evaluated the Universal Medication Schedule (UMS) across four major SFHN prescribing sites to help patients better understand medication instructions.^7,8 Results showed that, compared with patients who received standard instructions, patients who received UMS instructions were more likely to have adequate medication adherence (defined as taking meds 5 or more days in the prior week).¹

ASCENT represents one of the largest scale PSLLs completely situated in a safety-net setting that serves racially and ethnically diverse, publicly insured, low-income patients. Safety-net health systems are uniquely challenged by resource constraints and technology limitations. Approaches like those undertaken by ASCENT, which iteratively incorporate the unique context of a specific setting using design and systems engineering methodologies, can help health systems address these challenges and improve patient safety.¹

To date, this PSLL's work has resulted in at least 34 peer-reviewed journal publications, with nearly 200 citations in other publications.

Publications

2020

• Fontil V, et al. Evaluation of a health information technology-enabled panel management platform to improve anticoagulation control in a low-income patient population: protocol for a quasi-experimental design. JMIR Res Protoc 2020;9(1):e13835.
• Hickey MD, et al. Customized registry tool for tracking adherence to clinical guidelines for head and neck cancers: protocol for a pilot study. Pilot Feasibility Stud 2020;6:16.
• Lyles CR, et al. Using electronic health record portals to improve patient engagement: research priorities and best practices. Ann Intern Med 2020;172(11 Suppl):S123-S129.
• Patterson ES, Su G, Sarkar U. Reducing delays to diagnosis in ambulatory care settings: a macrocognition perspective. Appl Ergon 2020;82:102965.

2019

• Cedars B, et al. An electronic registry to improve adherence to active surveillance monitoring among men with prostate cancer at a safety-net hospital: protocol for a pilot study. Pilot Feasibility Stud 2019;5:101.
• Cherian R, et al. Standardization in diverse populations: implementation of evidence-based practices in a safety-net setting. Health Lit Res Pract 2019;3(1):e43-e46.
• Fontil V, et al. Testing and improving the acceptability of a web-based platform for collective intelligence to improve diagnostic accuracy in primary care clinics. JAMIA Open 2019;2(1):40-8.
• Gupta K, et al. Decisions and repercussions of second victim experiences for mothers in medicine (SAVE DR MoM). BMJ Qual Saf 2019;28(7):564-73.
• Khoong EC, et al. Perspectives of English, Chinese, and Spanish-speaking safety-net patients on clinician computer use: qualitative analysis. J Med Internet Res 2019;21(5):e13131.
• Kith G, et al. Defining and measuring adherence in observational studies assessing outcomes of real-world active surveillance for prostate cancer: a systematic review. Eur Urol Oncol 2019 Jul 6;S2588-9311(19)30084-7.
• Lee JS, et al. Follow-up of incidental pulmonary nodules and association with mortality in a safety-net cohort. Diagnosis (Berl) 2019;6(4):351-9.
• Lin SC, et al. Are patients electronically accessing their medical records? Evidence from national hospital data. Health Aff (Millwood) 2019;38(11):1850-7.
• Lyles CR, et al. A randomized trial to train vulnerable primary care patients to use a patient portal. J Am Board Fam Med 2019;32(2):248-58.
• Lyson HC, et al. A qualitative analysis of outpatient medication use in community settings: observed safety vulnerabilities and recommendations for improved patient safety. J Patient Saf 2019 Mar 13;10.1097/PTS.0000000000000590. Online ahead of print.
• Nouri SS, et al. Assessing mobile phone digital literacy and engagement in user-centered design in a diverse, safety-net population: mixed methods study. JMIR Mhealth Uhealth 2019;7(8):e14250.
• Sadasivaiah S, et al. Disparities in patient-reported interest in web-based patient portals: survey at an urban academic safety-net hospital. J Med Internet Res 2019;21(3):e11421.
• Schmajuk G, et al. Pneumocystis jirovecii pneumonia (PJP) prophylaxis patterns among patients with rheumatic diseases receiving high-risk immunosuppressant drugs. Semin Arthritis Rheum 2019;48(6):1087-92.

2018

• Cherian R, et al. Efficiency, efficacy, and power in the implementation of a medication adherence aid. Health Lit Res Pract 2018;2(3):e128-e131.
• Giardina TD, et al. Learning from patients' experiences related to diagnostic errors is essential for progress in patient safety. Health Aff (Millwood) 2018;37(11):1821-7.
• Khoong EC, et al. Implementation of patient-centered prescription labeling in a safety-net ambulatory care network. Am J Health Syst Pharm 2018;75(16):1227-38.
• Matta GY, et al. Finding meaning in medication reconciliation using electronic health records: qualitative analysis in safety net primary and specialty care. JMIR Med Inform 2018;6(2):e10167.
• Ratanawongsa, N et al. Certified medical interpreters’ perspectives on relationship-centered communication in safety-net care. MedEdPublish 2018;7(3):31.
• Ratanawongsa N, et al. Language-concordant automated telephone queries to assess medication adherence in a diverse population: a cross-sectional analysis of convergent validity with pharmacy claims. BMC Health Serv Res 2018;18(1):254.
• Ratanawongsa N, et al. Reducing misses and near misses related to multitasking on the electronic health record: observational study and qualitative analysis. JMIR Hum Factors 2018;5(1):e4.

2017

• Clarity C, et al. Clinician perspectives on the management of abnormal subcritical tests in an urban academic safety-net health care system. Jt Comm J Qual Patient Saf 2017;43(10):517-23.
• Issaka RB, et al. Inadequate utilization of diagnostic colonoscopy following abnormal FIT results in an integrated safety-net system. Am J Gastroenterol 2017;112(2):375-82.
• Lee SY, et al. Designing and implementing an electronic patient registry to improve warfarin monitoring in the ambulatory setting. Jt Comm J Qual Patient Saf 2017;43(7):353-60.
• Lowry C, et al. Primary care scribes: writing a new story for safety net clinics. BMJ Open Qual 2017;6(2):e000124.
• Luxenberg A, et al. Efficiency and interpretability of text paging communication for medical inpatients: a mixed-methods analysis. JAMA Intern Med 2017;177(8):1218-20.
• McDonald KM, et al. Implementation science for ambulatory care safety: a novel method to develop context-sensitive interventions to reduce quality gaps in monitoring high-risk patients. Implement Sci 2017;12(1):79.
• Ratanawongsa N, et al. The challenges of electronic health records and diabetes electronic prescribing: implications for safety net care for diverse populations. J Diabetes Res 2017;2017:8983237.
• Ratanawongsa N, et al. Multitasking and silent electronic health record use in ambulatory visits. JAMA Intern Med 2017;177(9):1382-5.
• Sadasivaiah S, et al. Improving best possible medication history with vulnerable patients at an urban safety net academic hospital using pharmacy technicians. BMJ Open Qual 2017;6(2):e000102.
• Sarkar U, et al. Changes in medication use after dementia diagnosis in an observational cohort of individuals with diabetes mellitus. J Am Geriatr Soc 2017;65(1):77-82.
• Schmajuk G, et al. Using health-system-wide data to understand hepatitis B virus prophylaxis and reactivation outcomes in patients receiving rituximab. Medicine (Baltimore) 2017;96(13):e6528.

2016

• Giardina TD, et al. Online public reactions to frequency of diagnostic errors in US outpatient care. Diagnosis (Berl) 2016;3(1):17-22.
• Mirsky JB, et al. A mixed-methods study of patient-provider e-mail content in a safety-net setting. J Health Commun 2016;21(1):85-91.
• Mirsky JB, et al. Readability assessment of patient-provider electronic messages in a primary care setting. J Am Med Inform Assoc 2016;23(1):202-6.
• Patterson ES, et al. Characterizing a naturalistic decision making phenomenon: loss of system resilience associated with implementation of new technology. J Cogn Eng Decis Mak 2016;10(3):229-43.

2015

• Lyles C, Schillinger D, Sarkar U. Connecting the dots: health information technology expansion and health disparities. PLoS Med 2015;12(7):e1001852.
• Lyles CR, Sarkar U. Health literacy, vulnerable patients, and health information technology use: where do we go from here? J Gen Intern Med 2015;30(3):271-2.

References

1. Sarkar U., Final Report: Building an Ambulatory Patient Safety Learning Laboratory for Diverse Populations: The San Francisco Ambulatory Safety CEnter for iNnovaTion (ASCENT). San Francisco:.University of California; 2021. pp. 1-20.
2. Lee SY, et al. Designing and implementing an electronic patient registry to improve warfarin monitoring in the ambulatory setting. Jt Comm J Qual Patient Saf 2017;43(7):353-60.
3. Hickey MD, et al. Customized registry tool for tracking adherence to clinical guidelines for head and neck cancers: protocol for a pilot study. Pilot Feasibility Stud 2020 Feb 7;6:16.
4. Cedars B, et al. An electronic registry to improve adherence to active surveillance monitoring among men with prostate cancer at a safety-net hospital: protocol for a pilot study. Pilot Feasibility Stud 2019 Aug 14;5:101.
5. Patterson ES, Su G, Sarkar U. Reducing delays to diagnosis in ambulatory care settings: a macrocognition perspective. Appl Ergon 2020 Jan;82:102965.
6. Fontil V, et al. Evaluation of a health information technology-enabled panel management platform to improve anticoagulation control in a low-income patient population: protocol for a quasi-experimental design. JMIR Res Protoc 2020;9(1):e13835.
7. Kith G, et al. Defining and measuring adherence in observational studies assessing outcomes of real-world active surveillance for prostate cancer: a systematic review. Eur Urol Oncol 2019 Jul 6;S2588-9311(19)30084-7. Online ahead of print.
8. Yu K, et al. Gaps in treatment and surveillance: head and neck cancer care in a safety-net hospital. OTO Open 2020;4(1):2473974X19900761.