Self-rated health: patterns in the journeys of patients with multi-morbidity and frailty Carmel Mary Martin MBBS PhD MSc FAFPHM MRCGP FRACGP Associate Professor and Visiting Academic, Public Health and Primary Care, Trinity College Dublin, Dublin, Co Dublin, Ireland Keywords evaluation, health services research, patient-centred care Correspondence Dr Carmel Mary Martin Public Health and Primary Care Trinity College Dublin 81 The Waxworks, Rathborne Rd, Ashtown Dublin, Co Dublin D 15 Ireland Accepted for publication: 27 March 2014 doi:10.1111/jep.12133 Abstract Rationale, aims and objectives Self-rated health (SRH) is a single measure predictor of hospital utilization and health outcomes in epidemiological studies. There have been few studies of SRH in patient journeys in clinical settings. Reduced resilience to stressors, reflected by SRH, exposes older people (complex systems) to the risk of hospitalization. It is proposed that SRH reflects rather than predicts deterio- rations and hospital use; with low SRH autocorrelation in time series. The aim was to investigate SRH fluctuations in regular outbound telephone calls (average biweekly) to patients by Care Guides. Methods Descriptive case study using quantitative autoregressive techniques and qualita- tive case analysis on SRH time series. Fourteen participants were randomly selected from the Patient Journey Record System (PaJR) database. The PaJR database recorded 198 consecutively sampled older multi-morbid patients journeys in three primary care settings. Analysis consisted of triangulation of SRH (0 very poor – 6 excellent) patterns from three analyses: SRH graduations associations with service utilization; time series modelling (autocorrelation, and step ahead forecast); and qualitative categorization of deteriorations. Results Fourteen patients reported mean SRH 2.84 (poor-fair) in 818 calls over 13 ± 6.4 months of follow-up. In 24% calls, SRH was poor-fair and significantly associated with hospital use. SRH autocorrelation was low in 14 time series (-0.11 to 0.26) with little difference (χ 2 = 6.46, P = 0.91) among them. Fluctuations between better and worse health were very common and poor health was associated with hospital use. It is not clear why some patients continued on a downward trajectory, whereas others who destabilized appeared to completely recover, and even improved over time. Conclusion SRH reflects an individual’s complex health trajectory, but as a single measure does not predict when and how deteriorations will occur in this study. Individual patients appear to behave as complex adaptive systems. The dynamics of SRH and its influences in destabilizations warrant further research. Introduction Self-rated health (SRH) is well documented as a valid measure of personal health states. It is arguably the best single measure pre- dictor of death, service use, institutionalization and hospitalization in older cohorts [1,2]. Epidemiological cross-sectional and time series studies confirm the utility of SRH as a single measure, but very few studies of SRH at clinically relevant time intervals have been published. According to Jylhä and others, SRH represents an individual’s unique access to their own bodily sensations and their meanings [3]. There is emerging evidence that SRH reflects impor- tant internal functioning such as inflammatory processes [3]. SRH correlates with changes in inflammatory markers in aging cohorts [4]. Aging and chronic illness is associated with a decline of adaptive immunity to address chronic internal and external stresses [5]. Personal experience narratives developed through conversa- tion have also been recognized as providing explanatory under- standings of patient journeys [6,7]. Health services’ performance assessment and financial penalties are being driven by the need to reduce expensive hospital utiliza- tion and institutionalization internationally. Thus, there is consid- erable impetus to better predict deteriorations in high-risk patient journeys in order to intervene in a timely but minimally expensive manner. Current models of post-acute care and care management Journal of Evaluation in Clinical Practice ISSN 1365-2753 Journal of Evaluation in Clinical Practice (2014) © 2014 John Wiley & Sons, Ltd. 1