Patient experience of in-center hemodialysis: advanced assessment toward more comprehensive and tailored care
Creators: name: Spezia, Nicola
Publisher: name: Zenodo
Year: 2023
Subjects: Patient Experience
In-center hemodialysis
Latent Class Analysis
AIES2022

description: Abstract presentation at the 27th Annual Conference of the Italian Health Economics Association Background<br> Multidimensional and evidence-based measures of performance are increasingly required to assess and improve the quality of health care delivery [1]. One of the backbones of these measures should be the inclusion of the perspective of patients [1,2]. Among the different forms to elicit patients’ perspectives, patient experience describes “patients’ perceptions of the range of interactions they have with the health care system” [3]. These include several aspects that are highly important to patients, such as the provision of medical information or communication and relationships with health professionals. Patient experience provides an assessment of the quality of these different elements of health care delivery directly from the point of view of patients. Subsequently, this information can be used to stimulate quality improvement interventions in the areas in which poor experiences are reported. In this way, patient experience can move health performance measurement systems toward a person-centered approach [2,4], measuring and providing information to improve “what matters most” to patients besides appropriate medical treatments [5]. For these reasons, patient experience is increasingly recognized as a key indicator of health care quality [3,5].<br> Despite the growing interest and implementation of this measure, the actual use of patient experience to improve the quality of care and health services is limited [6–9]. Specifically, patient experience data —which are usually collected through surveys— remain often unused after collection [6]. This might be due to different elements of organizational, attitudinal, contextual, and cultural inertia [7–9]. However, there is also a need to enhance the interpretation of patient experience data [6], requiring the introduction of new techniques to extract more intelligible, meaningful, and actionable information from them. In this sense, a relevant role could be played by those methods creating linkages between different measures of health care quality and capable of segmenting patient samples [8]. Linking different quality measures enables data triangulation, allowing patient experience assessment to be used in more holistic quality improvement plans. Segmentation, instead, allows identifying what different patient subgroups need and value, which may account for significant differences and peculiarities. In this way, patient experience can provide valuable information to design and implement targeted interventions to address the specific needs and concerns of each subgroup. Therefore, patient experience assessment could be enhanced from a perspective of both more comprehensive and tailored care. This may be crucial to increase the use of patient experience in driving quality improvement in health care.<br> Setting<br> This study is carried out within the Interreg project “InterACTIVE–HD 2.0”, which aims to improve the quality of life of patients undergoing in-center hemodialysis treatment along the Italian-Swiss border. Five public hospitals are involved in the project: ASST Lariana (Como), ASST Sette Laghi (Varese), ASST Valtellina e Alto Lario (Sondrio), Ente Ospedaliero Cantonale (Lugano), and Kantonsspital Graubünden (Chur).<br> Objective<br> This study aims to provide an advanced analysis of the patient experience of in-center hemodialysis. For this purpose, the specific experience profiles of different patient subgroups will be identified and associated with other measures of health care quality such as patient satisfaction with care.<br> Methods<br> Patient experiences of hemodialysis have been collected through a cross-sectional questionnaire composed of two sections: “nephrologists” and “dialysis nurses”. The survey included also two items (one for each survey section) measuring the overall satisfaction with care using a score ranging from 1 (worst satisfaction) to 10 (best satisfaction). The latent class analysis (LCA) statistical model will be employed to analyze survey data. This innovative technique has been recently implemented in the study of patient experience allowing the identification of distinctive subgroups with specific experience profiles, sociodemographic characteristics, and levels of overall satisfaction with care [10]. LCA is composed of three sequential steps: (1) independent subgroups (classes) definition using a stepwise procedure and statistical fit indexes, (2) classes’ characterization with sample’s descriptive variables through multinomial regressions, and (3) association and comparison of an outcome measure between classes using statistical hypothesis testing.<br> Results<br> In total, 403 surveys have been collected. Men represented 71% of the sample, 70% of patients were 65 years or older, 66% have been treated with dialysis for at least two years, and the percentage of respondents who described their physical and mental health status as “poor” or “bad” was equal to 46% and 23% respectively. Patients described a fairly high level of satisfaction with the received care (median values equal to 8 and 9 for nephrologists and dialysis nurses respectively). Overall positive experiences were reported for the interactions with nurses, especially when considering communication, availability, and support. Poorer experiences were described concerning nephrologists. Specifically, patients reported nephrologists not dedicating enough time to them during different interactions (such as the provision of medical information).<br> Data analysis using the LCA model is currently underway.<br> References<br> 1. Vainieri M, Noto G, Ferre F, Rosella LC. A performance management system in healthcare for all seasons? International Journal of Environmental Research and Public Health. 2020;17(15):1–10. <br> 2. Nuti S, Noto G, Vola F, Vainieri M. Let’s play the patients music: A new generation of performance measurement systems in healthcare. Management Decision. 2018;56(10):2252–72. <br> 3. Rhee CM, Brunelli SM, Subramanian L, Tentori F. Measuring patient experience in dialysis: a new paradigm of quality assessment. Journal of Nephrology. 2018;31(2):231–40. <br> 4. Nuti S, De Rosis S, Bonciani M, Murante AM. Rethinking healthcare performance evaluation systems towards the people-centredness approach: Their pathways, their experience, their evaluation. Healthcare Papers. 2017;17(2):56–64. <br> 5. Cavanaugh KL. Patient Experience Assessment is a Requisite for Quality Evaluation: A Discussion of the In-Center Hemodialysis Consumer Assessment of Health Care Providers and Systems (ICH CAHPS) Survey. Seminars in Dialysis. 2016;29(2):135–43. <br> 6. Coulter A, Locock L, Ziebland S, Calabrese J. Collecting data on patient experience is not enough: They must be used to improve care. BMJ (Online). 2014;348(March):1–4. <br> 7. Gleeson H, Calderon A, Swami V, Deighton J, Wolpert M, Edbrooke-Childs J. Systematic review of approaches to using patient experience data for quality improvement in healthcare settings. BMJ open. 2016;6(8):e011907. <br> 8. Flott KM, Graham C, Darzi A, Mayer E. Can we use patient-reported feedback to drive change? the challenges of using patient-reported feedback and how they might be addressed. BMJ Quality and Safety. 2017;26(6):502–7. <br> 9. Sheard L, Peacock R, Marsh C, Lawton R. What’s the problem with patient experience feedback? A macro and micro understanding, based on findings from a three-site UK qualitative study. Health Expectations. 2019;22(1):46–53. <br> 10. Spezia, N., Soncin M., Masella, C., &amp; Agasisti T. 2022 Studying the Experience of Care Through Latent Class Analysis An Application to Italian Neonatal Intensive Care Units Journal of Patient Experience, 9 23743735221107231
description: {"references": ["Coulter, A., Locock , L., Ziebland , S., &amp; Calabrese, J. (2014). Collecting data on patient experience is not enough: they must be used to improve Bmj 348", "Flott , Kelsey Margaret, et al. \"Can we use patient reported feedback to drive change? The challenges of using patient reported feedba ck and how they might be addressed.\" BMJ quality &amp; safety 26.6 (2017): 502 507.", "Sheard, L., Marsh, C., O'Hara, J., Armitage, G., Wright, J., &amp; Lawton, R. (2017). The patient feedback response framework unders tanding why UK hospital staff find it difficult to make improvements based on patient feedback: a qualitative study. Social s cie nce &amp; medicine, 178, 19 27. Sheard, L.,", "Sheard, L., Peacock, R., Marsh, C., &amp; Lawton, R. (2019). What's the problem with patient experience feedback? A macro and mic ro understanding, based on findings from a three\u2010site UK qualitative study. Health Expectations , 22(1), 46 53.", "Spezia, N., Soncin M., Masella, C., &amp; Agasisti T. 2022 Studying the Experience of Care Through Latent Class Analysis An Application to Italian Neonatal Intensive Care Units Journal of Patient Experience, 9 23743735221107231"]}