ABSTRACT
Objective: This study aimed to use the Person-Centered Coordinated Care Experience Questionnaire (P3CEQ) to assess the experience of person-centered coordinated care among people with long-term conditions in the Balearic Islands, Spain. Methods: Over 1300 participants receiving treatment for chronic conditions or HIV pre-exposure prophylaxis were invited to complete the P3CEQ and a socio-demographic questionnaire, both administered electronically via the Naveta app. The P3CEQ assesses the key domains of the P3C through an 11-item questionnaire. Items 1, 2, 3, 4, 5, 8, 9 and 10 assess specifically person-centredness (PC subscale), while items 5, 6, 7, 8 and 9 measure care coordination (CC subscale; question 7 includes 4 sub-questions to specifically assess care plans). Descriptive statistics were used to summarize patient characteristics and P3CEQ items scores. Data analysis included chi-squared test of independence, Student's t-test and analysis of variance test. Pairwise comparisons were adjusted by Bonferroni correction. Results: The P3CEQ and a socio-demographic questionnaire were sent to 1313 individuals (651 men, 657 women, 5 'other gender'). A response rate of 35.34% was achieved, with 464 P3CEQ responders (223 men and 241 women). Significant differences in response rates were observed by age, smoking status, alcohol consumption, membership of patient organizations, and use of alternative medicine. Care planning was rated significantly lower than other measured domains. Women experienced less person-centered care than men (16.64 vs 17.91) and rated care coordination worse than their male counterparts (9.18 vs 10.23). There were also differences in scores between medical condition types, with cancer and inflammatory bowel disease patients rating highest for both person-centered care (21.20 and 19.13, respectively) and care coordination (10.70 vs 10.88, respectively). Patients with skin and rheumatic diseases rated lowest their experience of person-centered care. People with higher education and those employed or studying experienced better person-centeredness. Conclusion: Using the P3CEQ, we detected significant differences in the care experiences of people with chronic conditions, suggesting the need to address potential gender biases, social inequalities, and the poorer ratings observed for certain conditions in the study population.
ABSTRACT
BACKGROUND: Patient-reported outcome and experience measures can play a critical role in providing patient-centered and value-based health care to a growing population of patients who are chronically ill. Value-based telemedicine platforms such as the Naveta initiative may facilitate the effective integration of these tools into health care systems. OBJECTIVE: This study aims to evaluate the response rate to electronic patient-reported outcome measures (ePROMs) and electronic patient-reported experience measures (ePREMs) among patients participating in the Naveta telemedicine initiative and its correlations with sociodemographic and clinical characteristics, as well as the evolution of the response rates over time. METHODS: Between January 1, 2021, and June 30, 2023, a total of 53,364 ePREMs and ePROMs for 20 chronic conditions were administered through the Naveta-Phemium platform. Descriptive statistics were used to summarize continuous and categorical variables. Differences in response rates within each sociodemographic variable were analyzed using logistic regression models, with significance assessed via chi-square and post hoc Tukey tests. Two-way ANOVA was used to examine the interaction between time interval and disease type on response rate evolution. RESULTS: A total of 3372 patients with severe chronic diseases from 64 public hospitals in Spain participated in the Naveta health questionnaire project. The overall response rate to ePROMs and ePREMs during the first 2.5 years of the Naveta initiative was 46.12% (24,704/53,364), with a baseline rate of 53.33% (7198/13,496). Several sociodemographic factors correlated with lower response rates, including male gender, older age, lower education level, frequent alcohol use, being a student, and not being physically active. There were also significant variations in response rates among different types of chronic conditions (P<.001), with the highest rates being for respiratory (433/606, 71.5%), oncologic (200/319, 62.7%), digestive (2247/3601, 62.4%), and rheumatic diseases (7506/12,982, 57.82%) and the lowest being for HIV infection (7473/22,695, 32.93%). During the first 6 months of follow-up, the response rates decreased in all disease types, except in the case of the group of patients with oncologic disease, among whom the response rate increased up to 100% (6/6). Subsequently, the overall response rate approached baseline levels. CONCLUSIONS: Recognizing the influence of sociodemographic factors on response rates is critical to identifying barriers to participation in telemonitoring programs and ensuring inclusiveness in patient-centered health care practices. The observed decline in response rates at follow-up may be due to survey fatigue, highlighting the need for strategies to mitigate this effect. In addition, the variation in response rates across chronic conditions emphasizes the importance of tailoring telemonitoring approaches to specific patient populations.
