Michelle Chiu, MD

All Publications

• Use of Voice-Based Conversational Artificial Intelligence for Basal Insulin Prescription Management Among Patients With Type 2 Diabetes: A Randomized Clinical Trial. JAMA network open Nayak, A., Vakili, S., Nayak, K., Nikolov, M., Chiu, M., Sosseinheimer, P., Talamantes, S., Testa, S., Palanisamy, S., Giri, V., Schulman, K. 2023; 6 (12): e2340232

  Abstract

  Optimizing insulin therapy for patients with type 2 diabetes can be challenging given the need for frequent dose adjustments. Most patients receive suboptimal doses and do not achieve glycemic control.To examine whether a voice-based conversational artificial intelligence (AI) application can help patients with type 2 diabetes titrate basal insulin at home to achieve rapid glycemic control.In this randomized clinical trial conducted at 4 primary care clinics at an academic medical center from March 1, 2021, to December 31, 2022, 32 adults with type 2 diabetes requiring initiation or adjustment of once-daily basal insulin were followed up for 8 weeks. Statistical analysis was performed from January to February 2023.Participants were randomized in a 1:1 ratio to receive basal insulin management with a voice-based conversational AI application or standard of care.Primary outcomes were time to optimal insulin dose (number of days needed to achieve glycemic control), insulin adherence, and change in composite survey scores measuring diabetes-related emotional distress and attitudes toward health technology and medication adherence. Secondary outcomes were glycemic control and glycemic improvement. Analysis was performed on an intent-to-treat basis.The study population included 32 patients (mean [SD] age, 55.1 [12.7] years; 19 women [59.4%]). Participants in the voice-based conversational AI group more quickly achieved optimal insulin dosing compared with the standard of care group (median, 15 days [IQR, 6-27 days] vs >56 days [IQR, >29.5 to >56 days]; a significant difference in time-to-event curves; P = .006) and had better insulin adherence (mean [SD], 82.9% [20.6%] vs 50.2% [43.0%]; difference, 32.7% [95% CI, 8.0%-57.4%]; P = .01). Participants in the voice-based conversational AI group were also more likely than those in the standard of care group to achieve glycemic control (13 of 16 [81.3%; 95% CI, 53.7%-95.0%] vs 4 of 16 [25.0%; 95% CI, 8.3%-52.6%]; difference, 56.3% [95% CI, 21.4%-91.1%]; P = .005) and glycemic improvement, as measured by change in mean (SD) fasting blood glucose level (-45.9 [45.9] mg/dL [95% CI, -70.4 to -21.5 mg/dL] vs 23.0 [54.7] mg/dL [95% CI, -8.6 to 54.6 mg/dL]; difference, -68.9 mg/dL [95% CI, -107.1 to -30.7 mg/dL]; P = .001). There was a significant difference between the voice-based conversational AI group and the standard of care group in change in composite survey scores measuring diabetes-related emotional distress (-1.9 points vs 1.7 points; difference, -3.6 points [95% CI, -6.8 to -0.4 points]; P = .03).In this randomized clinical trial of a voice-based conversational AI application that provided autonomous basal insulin management for adults with type 2 diabetes, participants in the AI group had significantly improved time to optimal insulin dose, insulin adherence, glycemic control, and diabetes-related emotional distress compared with those in the standard of care group. These findings suggest that voice-based digital health solutions can be useful for medication titration.ClinicalTrials.gov Identifier: NCT05081011.

  View details for DOI 10.1001/jamanetworkopen.2023.40232

  View details for PubMedID 38039007

• Patient-reported outcome measurement implementation in cancer survivors: a systematic review. Journal of cancer survivorship : research and practice Singhal, S., Dickerson, J., Glover, M. J., Roy, M., Chiu, M., Ellis-Caleo, T., Hui, G., Tamayo, C., Loecher, N., Wong, H. N., Heathcote, L. C., Schapira, L. 2022

  Abstract

  Patient-reported outcome measurements (PROMs) are increasingly used for cancer patients receiving active treatment, but little is known about the implementation and usefulness of PROMs in cancer survivorship care. This systematic review evaluates how cancer survivors and healthcare providers (HCPs) perceive PROM implementation in survivorship care, and how PROM implementation impacts cancer survivors' health outcomes.We systematically searched PubMed/MEDLINE, Embase, CINAHL, Web of Science, and Cochrane Database of Systematic Reviews from database inception to February 2022 to identify randomized and nonrandomized studies of PROM implementation in cancer survivors.Based on prespecified eligibility criteria, we included 29 studies that reported on 26 unique PROMs. The studies were heterogeneous in study design, PROM instrument, patient demographics, and outcomes. Several studies found that cancer survivors and HCPs had favorable impressions of the utility of PROMs, and a few studies demonstrated that PROM implementation led to improvements in patient quality of life (QoL), with small to moderate effect sizes.We found implementation of PROMs in cancer survivorship care improved health outcomes for select patient populations. Future research is needed to assess the real-world utility of PROM integration into clinical workflows and the impact of PROMs on measurable health outcomes.Cancer survivors accepted PROMs. When successfully implemented, PROMs can improve health outcomes after completion of active treatment. We identify multiple avenues to strengthen PROM implementation to support cancer survivors.

  View details for DOI 10.1007/s11764-022-01216-w

  View details for PubMedID 35599269

• FINDINGS FROM A NOVEL CANCER SURVIVORSHIP CLINIC EMBEDDED IN PRIMARY CARE: HIGH SATISFACTION AND IMPROVED PATIENT SELF-EFFICACY Chiu, M., Mai, A., Schapira, L., Kim, J. SPRINGER. 2021: S388-S389

  View details for Web of Science ID 000679443300965