Raising the Standard: Extending Patient-centered Care via Digital Healthcare

| May 1, 2021

by Jose Andres Reyes, MD; Andrew Bates, MD, FACS; and Dominick Gadaleta, MD, FACS, FASMBS

Dr. Reyes is a General Surgery Resident at New York Medical College at Metropolitan Hospital Center in New York, New York. Dr. Bates is Chief Minimally Invasive Surgery at South Shore University Hospital, Hofstra/Northwell in New York, New York. Dr. Gadaleta is Chair, Department of Surgery, South Shore University Hospital; Director, Metabolic and Bariatric Surgery, North Shore and South Shore University Hospitals, Northwell Health, Manhasset, New York; Associate Professor of Surgery, Zucker School of Medicine at Hofstra/Northwell in Hempstead, New York.

FUNDING: No funding was provided for this article.

DISCLOSURES: The authors report no conflicts of interest relevant to the content of this article.

Bariatric Times. 2021;18(5):14–15

Background: The Expansive Use of Digital Health was Advanced by COVID-19 and It Is Here to Stay

The COVID-19 pandemic propelled a paradigm shift in healthcare delivery towards digital health.1,2 To help prevent COVID-19 transmission, patients and healthcare providers were forced to adopt innovative techniques to access and deliver care, respectively, at a safe distance.3 But what became a necessity is rapidly turning into an essential instrument for the management of patients.

From the outset of the COVID-19 outbreak, the vast majority, if not all, of healthcare systems were ill-equipped to handle the healthcare crisis at hand.4 Overall, healthcare systems did not have robust technological infrastructures, experience, nor reimbursement models to swiftly transition from the traditional in-person doctor appointments to digital healthcare practices. Furthermore, for many, this was their first take with digital health after Congress and the United States Department of Health and Human Services made some strides to facilitate its use during the pandemic.5,6 The initial experience with digital health has been met with great fascination and acceptance, and experts anticipate that these emergent authorizations will persist post-COVID-19.7 Insight into the available technology has not only amplified its use but has also helped integrate digital health into patients’ livelihood. According to survey analysis, a majority of patients would choose virtual services for health and wellness advisories, routine appointments, and monitoring of ongoing health issues through at-home devices even after the COVID-19 pandemic.8 

Amplified use of digital health might be the silver lining of the COVID-19 pandemic. Health systems that are integrating digital health services into their groups’ daily workflow will be in a competitive position to meet patient demands.9 In view of the above, we examine how an artificial intelligence (AI) chatbot could be applied into our service’s workflow to engage and enable patients to access further information for the consideration of bariatric surgery. Moreover, we describe how the personalized text- or email-based program may be used to remotely monitor patients’ status and adherence to treatment plans after surgery.

The Technology

Northwell Health Chat is based on Conversa Health’s chatbot platform. This technology incorporates AI and machine learning to generate automated, customized chats with patients using their personal mobile device. These automated, targeted digital checkups are generated using clinical data and are sent to each patient based on clinical requirements. With the feedback generated from conversational AI, care teams can monitor patients’ clinical progress, gather patient-generated data that is included in electronic medical records (EMR), and triage patients to escalate care and allocate resources as needed.

The Colonoscopy Health Chat is already in effect to help reduce appointment cancelations. Up to 40 percent of patients, especially those in disadvantaged populations, either cancel or fail to show up for their scheduled colonoscopy.10 To tackle this problem, the Colonoscopy Health Chat, available in English and Spanish, provides educational material in a responsive, conversational way via email or text. The goal is to improve health literacy, provide information about bowel prep and how to accomplish it with minimal discomfort, as well as clarify any concerns with regard to the procedure to improve adherence to treatment.

Northwell has instituted the use of AI-powered chatbot to help reduce hospital readmission rates, monitor high-risk patients after myocardial infarction or cerebrovascular accident, as well as monitor patients receiving radiation therapy for cancer. Encouraging results has been observed with the application of similar technology in improving medication adherence rate in paitents with breast cancer.11 Furthermore, AI-based models might predict patients who are at high risk for radiation-induced toxicity, allowing specialists to take preventative measures to mitigate these potential side effects.12 These instances show that AI platforms are beneficial for both patients and providers.

The capability AI-based platforms have is exemplified by the home-spirometry program developed in part by the Center for Digital Health Innovation at the University of California San Francisco (UCSF).13 Launched within months after the onset of the COVID-19 pandemic, this program collects patient-derived data to promptly identify signs and symptoms consistent with chronic rejection after lung transplantation, while allowing immunosuppressed transplant patients to avoid unnecessary exposure to COVID-19 during hospital-based pulmonary function tests. The program consists of a personal spirometer that transmits data to the patient’s smartphone, which is in sync with an AI-powered chatbot. UCSF’s ultimate goal is to build a virtual platform that will symptom check and monitor medication adherence, lab results, exercise, nutrition, and other health metrics that are important for long-term superior lung transplant outcomes.

Application of Digital Health for Bariatric Surgery Patients

Research has demonstrated favorable long-term results with bariatric surgery, such as sustained weight loss, reduced mortality from diabetes, cardiovascular complications and cancer.14 However, many potential candidates from disadvantaged backgrounds lack access to bariatric surgery.15,16 Patients unaware of bariatric services can be educated on surgical options via automated customized chats. The AI platform could process consented medical records within the health system to filter potential patients that meet criteria for bariatric surgery. Subsequently, by streamlining clinical information, such as height, weight and comorbidities, AI can identify these patients and send a personalized text or email to extend further information to them. Patients that receive the information and are interested in learning more can interact with the AI chatbot and schedule an appointment.

Another potential application of the AI platform could be utilized during the postoperative phase. Once discharged after a bariatric procedure, patients would receive health checks inquiring about their status. Patients may report subjective and objective data, such as vital signs, finger sticks, pain levels, and wound care, which can be automatically populated into their EMR. Any alarming data can alert a provider for triaging and further evaluation. These applications allow patients to be closely monitored and give them the autonomy to participate in their care from the comfort of their home. Furthermore, scheduled conversational messages can be customized to help patients adhere to diet and treatment goals.

Conclusion

In sum, the COVID-19 pandemic propelled the implementation and use of virtual healthcare to meet the increasing demand for healthcare access. This abrupt change in healthcare delivery could potentially persist beyond COVID-19. Considering the continuing modernization in healthcare and the development of unprecedented events, AI and machine learning technology could be redesigned to engage and educate patients, help care teams monitor and manage patients at a distance, and triage patients in need of immediate attention to available local resources.

References

  1. Mann DM, Chen J, Chunara R, et al. COVID-19 transforms health care through telemedicine: evidence from the field. J Am Med Inform Assoc. 2020;27(7):1132–1135.
  2. Webster P. Virtual health care in the era of COVID-19. Lancet. 2020;395(10231):
    1180–1181.
  3. Schwamm LH, Estrada J, Erskine A, Licurse A. Virtual care: new models of caring for our patients and workforce. Lancet Digit Health. 2020;2(6):e282–e285.
  4. Keesara S, Jonas A, Schulman K. Covid-19 and health care’s digital revolution. N Engl J Med. 2020;382(e82).
  5. Public Law No. 116-123: Making emergency supplemental appropriations for the fiscal year ending September 30, 2020, and for other purposes. https://www.govinfo.gov/app/details/PLAW-116publ123/summary. Accessed March 6, 2020.
  6. Department of Health and Human Services. Notification of enforcement discretion for telehealth remote communications during the COVID-19 nationwide public health emergency. https://www.hhs.gov/hipaa/for-professionals/special-topics/emergency-preparedness/notification-enforcement-discretion-telehealth/index.html. Accessed March 6, 2020.
  7. Temesgen Z, DeSimone D, Mahmood M, et al. Health care after the COVID-19 pandemic and the influence of telemedicine. Mayo Clin Proc. 2020;95(9):S66–S68.
  8. Safavi K, Kalis B. How can leaders make recent digital health gains last?: Re-examining the Accenture 2020 digital health consumer survey. 2020. https://www.accenture.com/us-en/insights/health/leaders-make-recent-digital-health-gains-last. Accessed March 6, 2020.
  9. Telehealth: A Path to Virtual Integrated Care. 2019. https://www.aha.org/center/emerging-issues/market-insights/telehealth/path-virtual-integrated-care. Accessed March 6, 2020.
  10. Davis L. Northwell launches chatbot to boost use of colonoscopy. conversahealth.com. 2019. https://www.northwell.edu/news/the-latest/northwell-launches-chatbot-to-boost-use-of-colonoscopy. Accessed March 6, 2020.
  11. Chaix B, Bibault J-E, Pienkowski A, et al. When chatbots meet patients: one-year prospective study of conversations between patients with breast cancer and a chatbot. JMIR Cancer. 2019;5(1).
  12. Isaksson L, Pepa M, Zaffaroni M, et al. Machine learning-based models for prediction of toxicity outcomes in radiotherapy. Fron Oncol. 2020;10(790).
  13. Hays S, Singer J. Center for Digital Health Innovation at UCSF. A mission toward early detection of lung transplant rejection: the UCSF health virtual lung transplant care program. May 12, 2020. https://www.centerfordigitalhealthinnovation.org/posts/a-mission-toward-early-detection-of-lung-transplant-rejection-the-ucsf-health-virtual-lung-transplant-care-program. Accessed March 6, 2020.
  14. Adams TD, Gress RE, Sherman SC, et al. Long-term mortality after gastric bypass surgery. N Engl J Med. 2007;357(9):
    753–761.
  15. Wallace AE, Young-Xu Y, Hartley D, Weeks WB. Racial, socioeconomic, and rural-urban disparities in obesity-related bariatric surgery. Obes Surg. 2010;20(10):
    1354–1360.
  16. Jones DB, Falahee BE. Equity in bariatric surgery: access and outcomes. Bariatric Times. 2018;15(3):8–11. 

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