Family characteristics in high and low health care utilization

Weimer, Sanford R.; Hatcher, Chris; Gould, Edward

doi:10.1016/0163-8343(83)90045-2

Cited by 23 publications

(9 citation statements)

References 19 publications

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“…2000c). Proposed mechanisms for frequent attendance occurring more in some families include poverty and deprivation (Wilson 1977, Campion & Gabriel 1984); presence of a doctor‐defined significant diagnosis leading to more consultations (Campion & Gabriel 1984); transmission of illness behaviour through families (Huygen 1978, Huygen 1988); psychological aspects of the dynamics of the family (Weimar et al . 1983) and ‘family memories’ of ill health going back generations, poor communication between professionals, and trivial reasons (Blaxter & Paterson 1982).…”

Section: Discussionmentioning

confidence: 99%

The use of primary, secondary, community and social care by families who frequently consult their general practitioner

Neal

Wickenden

Cottrell

et al. 2001

Health &Amp; Social Care in the Community

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There have been very few studies that have examined either the use of other health and social services by patients who frequently consult their general practitioner, or the patterns of service use of frequently attending families. This study has three aims: to quantify the number of contacts to primary, secondary, community and social services of families who frequently attend their general practitioner; to examine the temporal patterns of these contacts and the patterns of use within families; and to determine the nature of these contacts and how they were valued by patients and health professionals. Thirty-five individuals in seven families completed diaries of health service use for 8 weeks; records from primary and community care records were analysed; health professionals and patients provided satisfaction scores for their contacts. The data were compared to standard datasets. The subjects made far more consultations with all health services than predicted, and less than half of these were with the general practitioner. Thirty-two per cent of the contacts with staff based within the health centre were not reported on the diary sheets. Temporal patterns of consulting were apparent within the families. The "index frequent attenders" within each family had most contacts. The differences between professional groups for the nature of the contact were marked, with over two-thirds of general practitioner contacts being for "specific symptoms or problems", and over two-thirds of health visitor contacts being for "weight problems". These findings show that patients who make high use of general practitioners' services also have a large number of contacts for health reasons with a range of other health and social services. These need to be considered as an outcome measure for trials of intervention for frequent attendance. More work is needed to explore why some individuals and their families make high use of health services.

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Section: Discussionmentioning

confidence: 99%

The use of primary, secondary, community and social care by families who frequently consult their general practitioner

Neal

Wickenden

Cottrell

et al. 2001

Health &Amp; Social Care in the Community

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“…The relationship between family dysfunction and PCC has an explanation from the family's conceptual framework, where behaviours are learned, attitudes are formed and patterns of stress adaptation are developed, including patterns of utilization. 39 The most important source of social support in our culture is the family. This might explain the preponderance of APGAR score on the Duke-UNC scale in the final regression; moreover, both questionnaires had items that could overlap.…”

Section: Discussionmentioning

confidence: 99%

Patient psychosocial factors and primary care consultation: a cohort study

2007

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Background. The combined influence of psychological distress, family dysfunction and social support on primary care consultation (PCC) remains unclear.Objective. To build an explanatory model of PCC concerning users' psychosocial factors.Methods. We undertook a multicentre, prospective cohort study of a random sample of 1141 persons assigned to 113 GPs, belonging to 11 urban health centres in four Spanish cities (Seville, Malaga, Jaen and Granada), of whom 955 (84%) were interviewed in their homes. They were followed up for 1 year and then contacted again. After the second interview, 70 (7.3%) patients were excluded; accordingly, we measured the number of PCC of 885 valid patients using their medical charts.Results. A multilevel analysis was developed. The null model with three levels showed that 93.29% of the variability was explained by the patients, 1.56% by the GPs and 5.15% by the health centres. We selected a two-level model (patients and health centres) with random effects. The variables used in the multilevel analysis explained 48% of PCC, 36% at the patient level and 12% at the health centre level. Poor mental health (GHQ-28, partial correlation coefficient = 0.28) and family dysfunction (Family APGAR index, partial correlation coefficient = 0.26) were the most predictive variables, whereas social support (Duke-UNC-11, partial correlation coefficient = -0.14) lost significance in the multivariate analysis. Chronic illness seemed less relevant in our study, and only two predisposing factors were included in the equation: age and satisfaction with their doctor.Conclusions. Mental health and family function were the most important psychosocial factors predicting PCC. More comprehensive identification of psychosocial factors may enhance our understanding of PCC.

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“…First, the mean, although a legitimate measure of central tendency of a distribution of scores, may not yield a score that has sufficient conceptual meaningfulness to be useful. For example, mean scores do not reflect differences among family members based on age or developmental stage (19); parents' and children's scores are weighted equally (34); and they do not reflect differences of power, influence or investment of family members in the task. Although weighting family members' scores may make sense in some cases, such a process requires careful conceptual justification.…”

Section: Arithmetic Meanmentioning

confidence: 99%

Alternative Strategies for Creating “Relational” Family Data

et al. 1985

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A major problem facing family clinicians and researchers is creating data that will reflect the family as a unit. To address this problem, we present a framework for family assessment based on three measurement strategies: individual family member assessment, relational family assessment, and transactional family assessment. Within this context, we present several categories of methods for combining individual family member data into "relational" scores that reflect the couple or family as a unit. The problems and benefits of each method are presented, and it is suggested that the choice of method is dependent upon the content of the assessment, the theory underlying the content, and the statistical properties of the individual family member scores.

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Family characteristics in high and low health care utilization

Cited by 23 publications

References 19 publications

The use of primary, secondary, community and social care by families who frequently consult their general practitioner

The use of primary, secondary, community and social care by families who frequently consult their general practitioner

Patient psychosocial factors and primary care consultation: a cohort study

Alternative Strategies for Creating “Relational” Family Data

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