An Automated Email or Phone Survey System for Patients of Primary Care Practices: assessing mode preferences, response rates, and mode effect (Preprint)
BACKGROUND A growing number of health care practices are adopting software systems that link with their existing electronic medical records (EMRs) to generate outgoing phone calls, emails, or text notifications to patients for appointment reminders or practice updates. While practices are adopting this software technology for service notifications to patients, its use for collection of patient-reported measures is still nascent. OBJECTIVE This study assessed the mode preferences, response rates, and mode effect for a practice-based automated patient survey (APS) using phone and email modalities to patients of primary care practices. METHODS This cross-sectional study analysed responses and respondent demographics for a short, fully automated, telephone or email patient survey sent to individuals within 72 hours of a visit to their regular primary care practice. Each survey consisted of five questions drawn from a larger study’s patient survey which all respondents completed in the waiting room at the time of their visit. APS responses were linked to self-reported sociodemographic information provided on the waiting room survey including age, sex, reported income, and health status. RESULTS 871 patients from 87 primary care practices in British Columbia, Ontario, and Nova Scotia, Canada agreed to the APS and 470 patients (45%) completed all five questions on the automated survey. Email administration of the follow up survey was preferred over phone-based administration, except amongst patients aged 75 years and older. Overall, response rates for those who selected an emailed survey (61%) were higher than those who received the phone-survey (38%). This held true irrespective of the age, sex, or chronic disease status of individuals. Response rates were also higher for email compared to phone surveys for all income groups except the lowest income quintile which had similar response rates for phone and email modes. We observed moderate agreement between waiting-room survey responses and those obtained in the follow-up automated survey. However, overall agreement in responses was poor for two questions relating to care-coordination. CONCLUSIONS An automated practice-based patient experience survey achieved significantly different response rates between phone and email and increased response rates for email as income group rose. Potential mode effects for the different survey modalities may limit multi-modal survey approaches. An automated minimal burden patient survey could facilitate the integration of patient reported outcomes into care planning and service organisation, supporting the move of our primary care practices towards a more responsive, patient-centred, continual learning system. However, practices must be attentive to furthering inequities in healthcare by underrepresenting the experience of certain groups in decision-making based on the reach of different survey modes.