ArticleBMC health services research2012
Profiling the different needs and expectations of patients for population-based medicine: a case study using segmentation analysis.
Article in BMC health services research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Segmentation of health-care consumers: psychological determinants of subjective health and other person-related variables.BMC health services research · 2020Article
- Identifying optimal indicators and purposes of population segmentation through engagement of key stakeholders: a qualitative study.Health research policy and systems · 2020Article
- Overall satisfaction of health care users with the quality of and access to health care services: a cross-sectional study in six Central and Eastern European countries.BMC health services research · 2016Article
- Retraction: Profiling the different needs and expectations of patients for population-based medicine: a case study using segmentation analysis.BMC health services research · 2013Article
Corrections and comments
- Retracted
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThis study illustrates an evidence-based method for the segmentation analysis of patients that could greatly improve the approach to population-based medicine, by filling a gap in the empirical analysis of this topic. Segmentation facilitates individual patient care in the context of the culture, health status, and the health needs of the entire population to which that patient belongs. Because many health systems are engaged in developing better chronic care management initiatives, patient profiles are critical to understanding whether some patients can move toward effective self-management and can play a central role in determining their own care, which fosters a sense of responsibility for their own health. A review of the literature on patient segmentation provided the background for this research.
methodFirst, we conducted a literature review on patient satisfaction and segmentation to build a survey. Then, we performed 3,461 surveys of outpatient services users. The key structures on which the subjects' perception of outpatient services was based were extrapolated using principal component factor analysis with varimax rotation. After the factor analysis, segmentation was performed through cluster analysis to better analyze the influence of individual attitudes on the results.
resultsFour segments were identified through factor and cluster analysis: the "unpretentious," the "informed and supported," the "experts" and the "advanced" patients. Their policies and managerial implications are outlined.
conclusionsWith this research, we provide the following: - a method for profiling patients based on common patient satisfaction surveys that is easily replicable in all health systems and contexts;- a proposal for segments based on the results of a broad-based analysis conducted in the Italian National Health System (INHS).Segments represent profiles of patients requiring different strategies for delivering health services. Their knowledge and analysis might support an effort to build an effective population-based medicine approach.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.