Does systematic analysis of patient complaints and compensation cases at hospitals provide useful information to guide quality improvement? Experience from Denmark

BACKGROUND

Patient complaints and compensation cases are analysed individually and do not allow for organisational learning. Systematic information on complaint patterns needs evidence-based measures. The Healthcare Complaints Analysis Tool (HCAT) can systematically code and analyse complaints and compensation claims, but whether this information is useful for quality improvement is underexplored. We aim to explore if and how HCAT information is perceived useful to inform healthcare quality gaps.

METHODS

To explore the HCAT's usefulness for quality improvement purposes, we used an iterative process. We accessed all complaints relating to a large university hospital. Trained HCAT raters systematically coded all cases, using the Danish version of HCAT.

INTERVENTION

The intervention had four phases: (1) coding of cases, (2) education, (3) selection of HCAT analyses for dissemination, (4) 'dashboard' development and delivery of targeted HCAT reports. To study the interventions and phases, we used quantitative and qualitative approaches. The coding patterns were descriptively displayed on department and hospital level. The educational programme was monitored using passing rates, coding reliability checks and rater feedback. Online interviews recorded dissemination feedback. We used a phenomenological approach with thematised quotations from the interviews to analyse the usefulness of the information from cases coded.

RESULTS

We coded 5217 complaint cases (11 056 complaint points). The average case coding time was 8.5 min (95% CI 8.2 to 8.7). All four raters passed the online test with >80% correct answers. Using rater feedback, we handled 25 cases of doubt. None affected the HCAT structure or categories. Interviews verified the usefulness of analyses after expert group dissemination. Three themes were important: 'overview of complaints', 'learning from complaints' and 'listening to the patients'. Stakeholders perceived the 'dashboard' development as highly relevant.

CONCLUSION

Through the development process with several adjustments, stakeholders found the systematic approach useful for quality improvement. The hospital management evaluated the approach as promising and decided to test the approach in clinical practice.

Mortality is Written on the Face

BACKGROUND

It is unknown whether facial or surrounding (eg, hair and clothing) cues have the strongest influence on the perceived age of subjects in photographic images, and which drives links between perceived age and survival.

METHODS

In 2001, 187 Danish twin pairs (n = 374) aged 70+ years were photographed generating passport-type images. The faces of the twins in these images were swapped creating two new images per twin pair (748 images in total). Ten nurses rated the perceived age of the twin from the original and swapped facial images. The survival of the twins was determined through to the end of 2013.

RESULTS

Changing the face or its surrounding significantly changed the perceived age of the images, with only a marginal difference between their effect sizes (difference of 0.5 years, 95% confidence interval CI -0.1 to 1.1). Perceived age, adjusting for chronological age, and sex, was a predictor of survival up to 7 years (hazard ratio 1.17, 95% CI 1.10-1.25) and also 7-12 years (hazard ratio 1.06, 95% CI 1.00-1.12) after the photographs were taken. Where the older looking twin died first they had a significantly older looking face (1.4 years older, 95% CI 0.3-2.6) but not surrounding (0.3 years older, 95% CI -0.8 to 1.4) compared to where the older looking twin died second.

CONCLUSIONS

Facial visual cues but not hair or clothing cues drive the link between perceived age and survival.

Perceived age as clinically useful biomarker of ageing: cohort study

OBJECTIVE

To determine whether perceived age correlates with survival and important age related phenotypes.

DESIGN

Follow-up study, with survival of twins determined up to January 2008, by which time 675 (37%) had died.

SETTING

Population based twin cohort in Denmark.

PARTICIPANTS

20 nurses, 10 young men, and 11 older women (assessors); 1826 twins aged >or=70.

MAIN OUTCOME MEASURES

Assessors: perceived age of twins from photographs. Twins: physical and cognitive tests and molecular biomarker of ageing (leucocyte telomere length).

RESULTS

For all three groups of assessors, perceived age was significantly associated with survival, even after adjustment for chronological age, sex, and rearing environment. Perceived age was still significantly associated with survival after further adjustment for physical and cognitive functioning. The likelihood that the older looking twin of the pair died first increased with increasing discordance in perceived age within the twin pair-that is, the bigger the difference in perceived age within the pair, the more likely that the older looking twin died first. Twin analyses suggested that common genetic factors influence both perceived age and survival. Perceived age, controlled for chronological age and sex, also correlated significantly with physical and cognitive functioning as well as with leucocyte telomere length.

CONCLUSION

Perceived age-which is widely used by clinicians as a general indication of a patient's health-is a robust biomarker of ageing that predicts survival among those aged >or=70 and correlates with important functional and molecular ageing phenotypes.

Why some women look young for their age

The desire of many to look young for their age has led to the establishment of a large cosmetics industry. However, the features of appearance that primarily determine how old women look for their age and whether genetic or environmental factors predominately influence such features are largely unknown. We studied the facial appearance of 102 pairs of female Danish twins aged 59 to 81 as well as 162 British females aged 45 to 75. Skin wrinkling, hair graying and lip height were significantly and independently associated with how old the women looked for their age. The appearance of facial sun-damage was also found to be significantly correlated to how old women look for their age and was primarily due to its commonality with the appearance of skin wrinkles. There was also considerable variation in the perceived age data that was unaccounted for. Composite facial images created from women who looked young or old for their age indicated that the structure of subcutaneous tissue was partly responsible. Heritability analyses of the appearance features revealed that perceived age, pigmented age spots, skin wrinkles and the appearance of sun-damage were influenced more or less equally by genetic and environmental factors. Hair graying, recession of hair from the forehead and lip height were influenced mainly by genetic factors whereas environmental factors influenced hair thinning. These findings indicate that women who look young for their age have large lips, avoid sun-exposure and possess genetic factors that protect against the development of gray hair and skin wrinkles. The findings also demonstrate that perceived age is a better biomarker of skin, hair and facial aging than chronological age.

Perceived age as a biomarker of ageing: a clinical methodology

In a previous field-based study, how old one looks for one's age (perceived age) was found to be predictive of mortality in elderly individuals. In conjunction, perceived age is of relevance and interest to the layperson. Here, a clinical methodology for generating perceived age as a biomarker of facial ageing is detailed. The methodology utilises facial photographs of subjects to present images to large numbers of age assessors who are primarily nationals of the country of study origin. In five observational studies in five different countries involving 874 female subjects it was found that subject age and assessor gender, nationality, age and ageing expertise had little effect on the perceived age data generated. However, increasing the numbers of age assessors up to 50 substantially increased the reproducibility of the mean perceived age for an image and a minimum of 10 assessors were required to give reproducible data. This methodology was also compared to a methodology that utilises passport-type photographs of subjects typically taken in field studies. Although the perceived age data from the two types of images were more similar to each other than to chronological age, there was a marked difference between the two sets of data. Therefore, to allow meaningful comparisons across perceived age studies, the same type of image should be used for the generation of perceived age. In conclusion, the methodology detailed here has demonstrated that perceived age can be a reproducible measure when large numbers of adult age assessors are used and can be utilised globally in studies to investigate facial ageing.

Influence of environmental factors on facial ageing

BACKGROUND

A recent twin study has shown that 'looking old for one's age' is associated with increased mortality. Approximately 40% of the variation in perceived age is due to non-genetic factors.

OBJECTIVE

To examine environmental factors influencing perceived age controlling for diseases.

DESIGN

A twin study.

SETTING

In the 2001 wave of the population-based survey--the Longitudinal Study of Aging Danish Twins--participants provided information on a wide range of exposures and health indicators. Additionally, they were asked to have a face photograph taken.

SUBJECTS

A total of 1826 elderly (70+) twins who had a high-quality face photograph taken.

METHODS

Ten nurses assessed the visual age of each twin from the face photograph. The mean of the nurses' age estimates for each twin was used as the twin's perceived age. Multivariate linear regression and intrapair comparison (for intact twin pairs) were used for analyses.

RESULTS

Statistically significant determinants of facial ageing associated with high perceived age for men were smoking (P = 0.01), sun exposure (P = 0.02) and low body mass index (BMI) (P<0.005), while for women they were low BMI (P = 0.05) and low social class (P<0.005). The number of children (men) and marital status (P = 0.08) and depression symptomatology score (women) were borderline significantly associated with facial ageing.

CONCLUSION

Our study confirms previous findings of a negative influence of sun exposure, smoking and a low BMI on facial ageing. Furthermore, our study indicates that high social status, low depression score and being married are associated with a younger look, but the strength of the associations varies between genders.

Hair Loss Among Elderly Men: Etiology and Impact on Perceived Age

BACKGROUND

Androgenetic alopecia is the most common type of hair loss in men, but little is known about the etiology of androgenetic alopecia in elderly men and its impact on perceived age. Here we used a population-based twin study of men aged 70+ to assess the magnitude of the genetic component affecting hair loss and to examine the association between baldness and perceived age.

METHODS

In the fourth wave of The Longitudinal Study of Aging Danish Twins we obtained digital photos of the face and photos of the vertex area of 739 elderly male twins, including 148 intact twin pairs. The degree of baldness and perceived age were assessed in each twin by five and nine nurses, respectively. The heritability of balding was estimated using structural-equation analysis, and it was tested whether baldness was associated with estimations of age.

RESULTS

The intrapair correlation of degree of balding was consistently higher for monozygotic than for dizygotic twin pairs regardless of the baldness categorization used, and structural-equation analysis revealed a heritability of 79% (95% confidence interval, 0.40--0.85) for the mean baldness index. The remaining variation could be attributed to non-shared environmental effects. There was only a very weak and statistically nonsignificant association between baldness and overestimation of age.

CONCLUSIONS

The majority of the variation in baldness in elderly men can be explained by genetic factors, and hair quantity has little impact on perceived age in elderly men.