Evaluation and significance of a digital assistant for patient history-taking and physical examination in telemedicine

Author:

Verma Neha1,Buch Bimal2,Pandya R S2,Taralekar Radha2,Masand Ishita1,Rangparia Hardik3,Katira J M3,Acharya Soumyadipta4

Affiliation:

1. Johns Hopkins University School of Medicine Division of Biomedical Informatics & Data Science, , 2024 East Monument St. S 1-200, Baltimore, MD 21205, USA

2. Intelehealth , 14A Shreeji Arcade, Panchpakhadi, Thane 400602, Maharashtra, India

3. District Health Department, Gibbson Middle School, Opposite Railway Station , Health Branch, Morbi 363641, Gujarat, India

4. Johns Hopkins University Center for Bioengineering Innovation & Design, , Clark Hall, Suite 208, 3400 Charles St, Baltimore, MD, USA

Abstract

  Introduction Assisted history-taking systems can be used in provider-to-provider teleconsultations to task-shift the collection of evidence-based medical history and physical exam information to a frontline health worker. We developed such a task-shifting digital assistant, called ‘Ayu’, for nurses in rural India to collect clinical information from a patient and share it with a remote doctor to arrive at an accurate diagnosis and triage decision. Materials & Methods We evaluated the ability of the task-shifting digital assistant to collect a comprehensive patient history by using 190 standardized patient case studies and evaluating the information recall of the assistant by a skilled clinician. Following this, we tested the ability of nurses to use the system by training and evaluating the system’s accuracy when used by 19 nurses in rural Gujarat, India. We also measured the diagnostic and triage accuracy based on the generated history note. Finally, we evaluated the system’s acceptability by using the Technology Acceptance Model framework. Results Ayu could capture 65% of patient history information and 42% of physical exam information from patient case studies. When used by nurses, the mean accuracy of the generated clinical note was 7.71 ± 2.42. Using the information collected by a nurse using Ayu, a primary care physician could arrive at the correct diagnosis in 74% of cases, and correct triage decision in 88% of cases. Overall, we saw a high acceptability from nurses to use the system. Conclusions Ayu can capture an acceptable proportion of clinical information and can aid in collecting an evidence-based medical history by task-shifting some of the early investigational steps. Further development of Ayu to increase its information retrieval ability and ease of use by health workers is needed.

Publisher

Oxford University Press (OUP)

Reference32 articles.

1. Patient safety and telephone medicine;Katz;J Gen Intern Med,2008

2. Variation in quality of urgent health care provided during commercial virtual visits;Schoenfeld;JAMA Intern Med,2016

3. Choice, transparency, coordination, and quality among direct-to-consumer telemedicine websites and apps treating skin disease;Resneck;JAMA dermatology,2016

4. The importance of the history and physical in diagnosis;Muhrer;Nurse Pract,2014

5. Contributions of the history, physical examination, and laboratory investigation in making medical diagnoses;Peterson;West J Med,1992

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