Psychosomatics 43:302-309, August 2002
© 2002 The Academy of Psychosomatic Medicine
Depression and Anxiety Impair Health-Related Quality of Life and Are Associated With Increased Costs in General Medical Inpatients
Francis Creed, M.A., M.D., F.R.C.P., F.R.C.Psych., F.Med.Sci.,
Richard Morgan, M.B., Ch.B., M.R.C.P., M.R.C.Psych.,
Magdalen Fiddler, B.Sc.,
Sarah Marshall, B.Sc., C.P.F.A., M.A.,
Else Guthrie, M.Sc., M.D., M.B., Ch.B., M.R.C.Psych., and
Allan House, B.Sc., M.B., B.S., M.R.C.P., M.R.C.Psych., D.M.
Received July 25, 2001; revised December 6, 2001; accepted January 17, 2002. From Psychological Medicine Research Group, University of Manchester; and University of Leeds. Address correspondence and reprint requests to Dr. Creed, Rawnsley Building, Manchester Royal Infirmary, Oxford Road, Manchester M13 9WL, United Kingdom; francis.creed{at}man.ac.uk (e-mail).
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ABSTRACT
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Two hundred sixty-three consecutive medical inpatients were studied to assess whether depression and anxiety are associated with increased costs and reduced health-related quality of life. Seventy-three (27.8%) had depressive/anxiety disorders, 107 were "subthreshold" cases, and 83 were controls. After adjustment for severity of physical illness, using the Duke Severity of Illness Scale, cases and subthreshold cases incurred greater mean health care costs than controls over the follow-up period: $8,541 (SE = $605) versus $5,857 (SE = $859), P = 0.012. There was significant impairment of health-related quality of life (SF36 scores) in cases and, to a lesser extent, in subthreshold cases compared to controls. This impairment persisted at follow-up, as did anxiety and depression, indicating the need for future intervention studies.
Key Words: Depression • Quality of Life
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INTRODUCTION
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Depressive and anxiety disorders are approximately twice as common in general hospital patients as they are in the general population.1 This should lead to additional help for these disorders in the general hospital, whereas, in fact, the presence of physical illness often leads to the mental health needs of patients being relatively ignored.1–5 This calls for more intervention studies, like those being performed in primary care,6–8 which demonstrate the benefits of detecting and treating anxiety and depressive disorders in general medical settings.9–12 Planning and executing such studies require considerable attention to a number of issues that will determine their outcome.11,13 These issues include the selection of patients, appropriate outcome measures (costs vs. health-related quality of life in the present climate of shortening length of stay), and adjustment for confounders.
Many previous studies of medical inpatients have not identified the specific effect of depressive disorders because they have sought to define the benefits of a consultation-liaison service on a range of psychiatric disorders; that is, they also included delirious and demented patients, which may have a profound effect on length of stay.11,14 One study differentiated the increased hospitalization associated with depression as opposed to cognitive impairment.15 If we are to assess the benefits of specific treatment for depressive and anxiety disorders, we must define first the increased health care use associated with these disorders.
Depressive disorders impair health-related quality of life,16–18 but the effect is not confined to major depression; it occurs also in mixed depressive/anxiety disorders, panic disorder, and "subthreshold" disorders, in which symptoms of depression and anxiety are present but insufficient to be classified as definite disorders.19–22 Not all reports agree, however, that subthreshold disorders are associated with increased costs.23
Studies of medical inpatients have tended to measure the effect of psychiatric disorders on length of hospital stay, but, with increased pressure on hospital beds, this may have become so brief that it is unlikely to be affected by mood state. A few studies have considered continuing primary health costs and the costs of readmissions in addition to costs associated with the index admission. These have shown a higher readmission rate for depressed patients, and the depression documented during hospitalization continues following discharge without attracting treatment from the general practitioner.2,15 Again, though, there are conflicting results.24 However, studies in primary care show clearly increased health care costs associated with both depressive and anxiety disorders even after controlling for the effects of medical comorbidity.10
Many studies of medical inpatients have not adequately adjusted for confounders, especially severity of medical illness, even though this may be the most important determinant of length of stay.11,13,14 There is no accepted and reliable way to do this; previous studies have used the Karnofsky Performance Status Scale, physician's rating of medical comorbidity, or the Chronic Disease score.15,23
In order to plan a future intervention study, we wished to quantify the degree to which depressive and anxiety disorders are associated with increased health care costs and impaired health-related quality of life among medical inpatients. We have therefore undertaken a prospective cohort study in which we identified patients admitted to general medical wards who had coexisting depression or anxiety and followed them up after discharge. We aimed to test the hypotheses that depressive and anxiety disorders at the time of admission are, after adjusting for the effect of severity of physical illness, associated with 1) increased length of stay, 2) greater health care costs during the 5 months following admission, and 3) poorer health-related quality of life at follow-up. We used a two-phase method of detecting psychiatric disorder, and, in view of the uncertainty regarding the appropriate threshold for defining psychiatric disorders in the medical population, we used definite psychiatric disorders defined according to ICD-10 as well as a lower criterion for "subthreshold" disorders.25
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METHODS
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The study was performed in the acute medical wards of a large teaching hospital based in an inner-city area with a socially deprived population. Consecutive patients admitted to these wards were included if they were living in Manchester, aged 18 years or more, admitted for more than 24 hours, and well enough to complete questionnaires and an interview. Patients were excluded if they had marked cognitive impairment (Mini-Mental State Examination score of 20 or less), were admitted primarily for a psychiatric reason (including overdose, alcohol withdrawal), were in the Intensive Therapy Unit, or were involved in another study. Time constraints meant that we could screen and recruit only up to 8 patients per day. Informed consent was obtained by all participants after a full explanation of the project. Ethical permission was obtained from Manchester Health Authority Research Ethics Committee (Central) CM/97/021.
All participants completed the Hospital Anxiety and Depression Scale,26 a self-report mood rating scale designed for use in patients with physical illness.27 All patients who scored over 10 on the Hospital Anxiety and Depression Scale (combined anxiety and depression scores) were interviewed using the Schedules for Clinical Assessment in Neuropsychiatry interview28 to derive an ICD-10 psychiatric diagnosis. Severity of disability directly resulting from physical illness was measured using the Karnofsky Performance Status Scale.29 The Duke Severity of Illness Scale30 was used to determine the number and severity of physical illnesses. Severe illness is given a high score on the Duke Scale and a low score on the Karnofsky Performance Status Scale.
Health-related quality of life was assessed using the Medical Outcome Study Short-Form 36 (SF-36).31 This has eight subscales, four concerned with physical function and pain and four concerned with aspects of mental health. A high score indicates good health-related quality of life. The SF-36 has been widely used in medical populations and has high internal consistency and reliability for British patients.18,32 This was completed at admission and again 5 months later. The 5-month follow-up was determined by the short duration of the grant available for the study.
Health care costs were derived for the 5 months following the date of admission. These included all costs associated with the initial hospital stay, any subsequent admissions, and all other contacts with primary and secondary care. Activity data were taken directly from the patient's hospital and primary care notes as all patients received professional health care solely from the UK National Health Service (NHS). Use of other services (e.g., home help) was derived from the patient interview using the Client Service Receipt Inventory.33 Cost data were then derived by applying appropriate unit costs to the service use data. These unit costs include appropriate overheads for the institution as well as the services provided. Cost data are expressed as hospital costs (inpatient stays, special investigations, day case attendances, accident and emergency, and outpatient visits), primary care costs (general practitioner surgery visits, home and emergency visits, and surgery nurse visits), and community costs (district nurse visits, home help, and community psychiatric nurse visits).
Statistical Analysis
The data were analyzed with the patients in three groups: people with a high Anxiety and Depression Scale score who met diagnostic criteria for depressive or anxiety disorders at Schedules for Clinical Assessment in Neuropsychiatry interview (referred to henceforth as "cases"), those with a high Hospital Anxiety and Depression Scale score who did not meet diagnostic criteria at interview ("subthreshold" cases), and those with a low Hospital Anxiety and Depression Scale score ("controls").
Statistical significance of differences between the three groups at baseline was assessed using the chi-square test for the categorical variables and analysis of covariance (ANCOVAR) for age and the questionnaire scales. The three groups were compared in terms of SF36 and Hospital Anxiety and Depression Scale scores at admission and at follow-up after adjusting for age, the seriousness of physical illness at admission using the Duke Severity of Illness score, social class, and benefit, using analysis of covariance. Where results were significant at the 5% level, post hoc multiple comparisons were carried out using Bonferroni adjustments.
Cost data are presented as means and standard errors to allow inferences to be made about the arithmetic mean and analyzed using the ANCOVAR to adjust for seriousness of physical illness. The cost data were highly positively skewed, and so the results were checked using bootstrap methods.35
All data were analyzed using the Statistical Package for the Social Sciences (SPSS), except bootstrapping, which used STATA.
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RESULTS
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Subjects
Five hundred and eighty-eight consecutive medical inpatient admissions met the clinical inclusion criteria; 222 were excluded because they were admitted on a day when eight patients had already been entered into the study. Of the remaining 366 patients, 63 (17.2%) refused, and 40 were discharged before complete data had been collected, leaving 263 patients (72% of the 366 eligible patients) who were included in the study. The mean age of the 263 patients was 61 years (age range from 18–98); 148 (56%) were female, and 116 (44%) were married or cohabiting. Two hundred and thirty-two were white, 17 black African-Caribbean, and eight South Asian origin; six belonged to other ethnic groups. Two hundred and forty-nine (94.6%) were admitted urgently. The 222 patients who were excluded because they were admitted on a day when eight patients had already been recruited were not significantly different from the 263 patients included in terms of age and sex.
Of the 263 subjects, 73 (27.8%) were definite "cases" of psychiatric disorder, 107 (40.7%) were "subthreshold" cases, and 83 (31.6%) were controls. The most frequent diagnosis of the 73 cases were depressive episode (n = 54) and panic disorder (n = 29) (the SCAN allows multiple diagnoses).
The baseline social and clinical characteristics are shown in Table 1. Compared to the other groups, the cases of psychiatric disorder were more likely to be female, unemployed, and in receipt of illness-related benefits, and they had more severe physical illness.
At follow-up, 19 had died, and of the remaining 244, we interviewed 218 (89%); 10 refused, and 16 had moved away without a forwarding address. The 218 patients followed up, and the remaining 26 surviving patients did not differ on baseline SF36 or Hospital Anxiety and Depression Scale scores. The patients who had died had a significantly lower Karnofsky score at admission than those who survived: 57.7 (SD) = 11.9 versus 68.4 (SD) = 16.1, P = 0.008. There was no significant difference on Duke score: 72.8 (SD) = 10.8 versus 70.8 (SD) = 11.0, respectively (P = 0.45).
Health-Related Quality of Life and Hospital Anxiety and Depression Scale Scores
The health-related quality of life (SF36) and Hospital Anxiety and Depression Scale scores adjusted for severity of physical illness are shown in Table 2 and Table 3 and Figure 1. The data in Table 2 and Table 3 relate to patients on whom complete data were available at both initial and follow-up assessment (n = 203). At admission cases had significantly lower scores (i.e., more impaired) than controls on every dimension of the SF36 after adjustment for severity of physical illness (Table 2 and Table 3). This pattern was maintained at follow-up except for role limitation (physical). Subthreshold cases showed significantly lower scores than controls on all but two dimensions at admission but only on two at follow-up.
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TABLE 2. Health-related quality of life and mood scores at admission and at 5-month follow-up; means and standard errors adjusted for gender, social class, social benefits, and severity of physical illness using the Duke Severity of Illness score (n = 203)
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TABLE 3. Health-related quality of life and mood scores at admission and at 5-month follow-up; means and standard errors adjusted for severity of physical illness using Karnofsky Performance Status (n = 203)
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FIGURE 1. Mean SF36 scores for physical and mental health dimensions at 5-month follow-up adjusted for severity of physical illness using Karnofsky Performance Status (n = 185), with population norms also shown.
aFrom the study by Garratt et al.33
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Figure 1 shows data at follow-up for the "physical" dimensions of the SF36. It can be seen that all participants scored well below population norms for this age group36 and cases have lowest scores. Figure 1 shows that control patients were similar to population norms on the mental health scale. Cases show marked impairment on the other subscale scores.
The adjusted follow-up Hospital Anxiety and Depression Scale scores were very similar to those at admission with the exception that the scores in controls slightly increased. Only 10 of the cases had a reduction of Hospital Anxiety and Depression Scale score of five or more at follow-up compared to admission score.
Length of Stay
The median total length of stay and interquartile range for the index admission and any further admissions during the 5-month follow-up period were cases 9 days (6–20), subthreshold cases 11 days (7–22), and controls 7 days (4–18). There was no significant difference between these groups after adjustment for severity of physical illness.
Costs
Health care costs in this sample were accounted for largely by hospital costs (Table 4). After adjustment for severity of physical illness, the cost differences across the three groups were significant (P = 0.013). Costs incurred by people with anxiety and depression (cases and subthreshold cases combined) were higher than controls (right-hand column, Table 4).
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TABLE 4. Comparison of health care costs; means and standard errors adjusted for gender, social class, social benefit, and severity of physical illness using the Duke Severity of Illness score (n = 196)
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DISCUSSION
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This is one of very few prospective cohort studies that shows an association between psychiatric comorbidity in medical patients and outcome after adjusting for severity of physical illness using standardized measures. There are several important findings. First, depressive/anxiety disorders are common, occurring in 27% of medical inpatients in an inner-city area. A further 41% had subthreshold disorders, which also impair health-related quality of life. Second, these disorders are persistent and are not transient indicators of distress while a person is in the hospital. Third, depressive and anxiety disorders are not associated with length of stay, but people with distress (i.e., those with depression/anxiety disorders together with patients who have subthreshold disorders) do incur greater total health care costs compared to those with a low Hospital Anxiety and Depression Scale score.
The proportion of cases of depressive/anxiety disorders in this sample (28%) was similar to that of comparable studies in Manchester, Verona, and London3,5,37 but higher than that of Oxford,2 presumably reflecting the social deprivation of Manchester. In inner-city areas, approximately a quarter of medical inpatients have two disorders—a physical and a psychiatric disorder, each of which independently impairs health-related quality of life; the effect appears to be approximately additive.17,18
The very low scores on the SF36 for the cases and subthreshold cases indicate profound impairment of health-related quality of life. After adjustment for severity of physical illness, SF36 scores in Table 2 and Table 3 show at least a 20-point difference between cases and controls, even on the variables that are not directly related to mental health, such as pain, physical limitation, and role functioning. The scores in this study are much lower than those recorded with physical illness alone36 or chronic depression,38 and it appears that during the 5 months following admission, there was little change in SF36 scores. Other studies have shown persistence of low scores on SF36 for outpatients with diabetes, heart disease, and comorbid depression and anxiety, including both minor and major depression.16,39,40
The marked difference between cases and controls on the variables such as pain and physical limitation probably reflects the effect depression has on pain perception and motivation for daily activities. It could be explained by these people having more serious physical illness, but we think this is unlikely, as the difference remained considerable after adjusting for severity of physical illness and as subthreshold cases had SF36 scores halfway between the cases and the noncases on many scales. Further longitudinal studies are needed to see whether SF36 scores improve after depression is treated; the persisting high Hospital Anxiety and Depression Scale scores at follow-up indicate the important opportunity to do this. One other study has shown persistently raised Hospital Anxiety and Depression scores associated with persistently raised disability scores following discharge from a general hospital with a pattern of results for cases and subthreshold cases very similar to those in this study.41
The numbers in this study are small for a full health economic analysis, but our findings indicate increased cost associated with distress. The highest health care costs were associated with subthreshold disorders; this may be a chance finding, as variation in cost is great. This finding relates to hospital and community costs, and it is not clear what drives these costs. General practitioner costs are more clearly driven by patients seeking treatment, and these costs were significantly higher in the cases. Our results correspond to the those in diabetes, where patients with marked and moderate depressive symptoms (corresponding to subthreshold disorders) incurred the highest costs in specialty services, but only those with marked symptoms incurred higher costs in primary care.42
The lack of an effect of depression on length of stay may reflect the short stay now usual in this hospital; mean length of stay in these medical wards has reduced from 11 days to 6 days over recent years (F. Ballardie, personal communication). Alternatively, the effect of psychiatric disorder on length of stay in previous studies may have been principally that associated with delirium and dementia rather than depression.
There are three methodological limitations to our study. First, we did not interview low Hospital Anxiety and Depression Scale score participants, and we may have missed a few who were cases. We think this unlikely in view of our low cutoff score. Second, there is no widely accepted single measure of severity of physical illness; we used the Duke scale but obtained similar results if we ran the analyses using the Karnofsky Performance Status Scale, which is a valid and reliable predictor of mortality43 (including in our study). Either scale may fail to detect all aspects of severity of physical illness associated with health care costs. Third, it was beyond the scope of this study to assess fully social factors such as degree of social support and employment status, which may be confounders; we adjusted for social class and receipt of social benefits as a proxy for such variables.
The importance of this study lies in the possibility it raises that we can improve health-related quality of life if depressive/anxiety disorders are treated. Such an intervention will need to be applied to patients with subthreshold disorders38,44 as well as those with definite psychiatric disorders if we are to determine whether psychological treatment can reduce health care costs as well as improve health-related quality of life in medical patients.
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ACKNOWLEDGMENTS
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This study was funded by the UK Medical Research Council and the North West Region R & D Directorate.
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ABSTRACT
INTRODUCTION
