Major depression in older medical inpatients predicts poor physical and mental health status over 12 months

General Hospital Psychiatry 29 (2007) 340 – 348

Major depression in older medical inpatients predicts poor physical and mental health status over 12 months☆ Jane McCusker, M.D., Dr.P.H. a,b,⁎, Martin Cole, M.D., F.R.C.P.(C) c,d , Antonio Ciampi, Ph.D. b , Eric Latimer, Ph.D. d,e , Sylvia Windholz, M.D., C.C.F.P. f , Eric Belzile, M.Sc. a a

Department of Clinical Epidemiology and Community Studies, St. Mary's Hospital, Montreal (Quebec), Canada H3T 1M5 b Department of Epidemiology and Biostatistics, McGill University, Montreal (Quebec), Canada H3T 1M5 c Department of Psychiatry, St. Mary's Hospital, Montreal, Montreal (Quebec), Canada H3T 1M5 d Department of Psychiatry, McGill University, Montreal (Quebec), Canada H3T 1M5 e Douglas Hospital Research Centre, Montreal, Montreal (Quebec), Canada H3T 1M5 f Division of Geriatric Medicine, Department of Family Medicine, Sir Mortimer B. Davis Jewish General Hospital, and McGill University, Montreal (Quebec), Canada H3T 1M5 Received 24 January 2007; accepted 22 March 2007

Abstract Objective: The aim of this study was to determine the 12-month effects upon physical and mental health status of a diagnosis of major or minor depression among older medical inpatients. Methods: Patients 65 years and older, admitted to the medical wards of two university-affiliated hospitals, with at most mild cognitive impairment, were screened for major and minor depression (Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition criteria). All depressed patients and a random sample of nondepressed patients were invited to participate. The physical functioning and mental health subscales of the Medical Outcomes Study 36-Item Short Form Health Survey (SF-36) were measured at baseline and at 3, 6 and 12 months. Results: Two hundred ten patients completed the SF-36 at baseline and at one or more follow-ups. In multiple linear regression analysis for longitudinal data, adjusting for baseline level of the SF-36 subscale outcome, severity of physical illness, premorbid disability, age, sex and other covariates, patients with major depression at baseline had lower SF-36 scores at follow-up, in comparison to patients with no depression [physical health, 9.22 (95% CI −15.52 to −2.93); mental health, 6.28 (95% CI −11.76 to −0.79)]. Conclusion: A diagnosis of major depression in cognitively intact older medical inpatients is associated with sustained poor physical and mental health status over the following 12 months. © 2007 Elsevier Inc. All rights reserved. Keywords: Aged; Depression; Health status; Longitudinal study

1. Introduction Despite its frequent occurrence [1] and poor prognosis [2], major depression in older medical inpatients is usually not detected or treated [3,4]. In part, this failure to detect

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This study was funded by Canadian Institutes for Health Research, Grants MOP82494 and MCT-15476. ⁎ Corresponding author. Department of Clinical Epidemiology and Community Studies, St. Mary's Hospital, 3830 Lacombe, Montreal (Quebec), Canada H3T 1M5. Tel.: +1 514 345 3511x5060; fax: +1 514 734 2652. E-mail address: [email protected] (J. McCusker). 0163–8343/$ – see front matter © 2007 Elsevier Inc. All rights reserved. doi:10.1016/j.genhosppsych.2007.03.007

and treat may reflect lack of clear knowledge about whether a diagnosis of depression in this population affects patients' long-term physical and mental health outcomes, independently of severity of physical illness and other factors. To date, most studies in hospitalized samples have used an outcome measure of physical disability [e.g., dependence in activities of daily living (ADL)] [5–7]. Use of a generic health status measure such as the Medical Outcomes Study 36-Item Short Form Health Survey (SF36) is a useful means of assessing the impact of a health problem on different dimensions of health status [8] and comparing this impact with population norms [9]. Although the SF-36 appears to perform well as a tool

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for monitoring the effect of outpatient treatment of depression on mental health outcomes [10], only one study to our knowledge has investigated the use of a generic health status measure among depressed older hospitalized patients [11]. This study was limited by a short (1 month) follow-up period, and the outcomes were not adjusted for comorbidity. Thus, the primary objective of this study was to determine the impact of major or minor depression on a generic health status measure, the SF-36, during the 12 months after admission, independent of baseline physical disability, comorbidity and other confounding variables. There is some evidence from community but not from inpatient samples that social network and support can buffer the negative effects of late life depression [12,13]. Therefore, a secondary objective was to determine whether the patient's social network or support modified the effects of depression diagnosis on the health status outcomes. Because we have reported separately on the effects of depression diagnosis on survival [14], patients who died during follow-up have been excluded from this study.

trial (RCT) that compared systematic detection and multidisciplinary management with usual care [18]. Because the intervention did not affect any of the outcomes at 6 or 12 months (including physical and mental health status), patients who participated in the RCT have been included in this analysis. The study protocol was approved by the research ethics committees of both hospitals. Patients with severe depression (clinical criteria) were referred to a specialist in geriatric psychiatry (M.C.) or a geriatrician (S.W.).

2. Methods

2.3. Measures

2.1. Study design

2.3.1. Depression The depressive disorders section of the DIS [17] was administered at the baseline research interview and at each follow-up. Patients were classified as having current (at least 2 weeks duration of symptoms) major, minor or no depression with DSM-IV criteria using the “inclusive” approach (symptoms counted towards the diagnosis regardless of the symptoms' origins, whether physical illness or depression) [19]. The interrater reliability of the DIS was assessed in a convenience sample of 28 patients at intervals throughout the study period, using independent simultaneous ratings by two or more raters, including the study psychiatrist (M.C.). Values of the kappa coefficient were .78 (95% CI 0.52–1.00) for a diagnosis of major depression vs. minor or no depression and .61 (95% CI 0.35–0.87) for a diagnosis of either major or minor vs. no depression.

The study was an observational, prospective study of a cohort of older medical inpatients, with oversampling of patients with a diagnosis of major or minor depression. Recruitment methods have been described in detail previously [1]. The study was conducted at two university-affiliated acute care Montreal hospitals, using random sampling from lists of consecutive, nonelective admissions of patients 65 years and older to the medical services (we focused on these admissions because of our interest in outcomes of depression in acutely medically ill patients.) The following were excluded: patients admitted to palliative care (because of expected survival of less than 6 weeks); those who did not speak or understand English or French or were otherwise unable to communicate; those who lived off the island of Montreal (due to difficulty of follow-up) and those admitted to the intensive care or cardiac monitoring units. Eligible patients were screened using the Short Portable Mental Status Questionnaire (SPMSQ) [15]; those with five or more errors (indicating moderate-severe cognitive impairment) [16] were excluded because the presence of such cognitive impairment complicates diagnosis and measurement of depression. Major and minor depression were diagnosed using the Diagnostic Interview Schedule (DIS) using Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria [17]. All depressed patients and a random sample of nondepressed patients were invited to participate in the longitudinal component of the study. At one of the hospitals, patients with major depression were invited to participate in a concurrent randomized controlled

2.2. Data collection Data were collected at the two hospitals using the same research staff and methods. Research assistants were blind to the patients' initial depression diagnosis. Patients were interviewed at baseline (as soon as possible after enrollment) and at 3, 6 and 12 months after enrollment. Other data sources included (1) review of patient medical charts; (2) abstraction of administrative databases at the two hospitals and (3) provincial hospital discharge, physician billing and prescription databases (all patients are covered by government health insurance for these services).

2.3.2. Health status The SF-36 was administered at all study baseline and follow-up interviews [8]. This widely used measure has demonstrated validity, internal consistency and retest reliability [20,21] and also performs well in depressed elderly [10]. Two summary measures, the Mental and Physical Component Summary Scales, and eight specific subscales can be computed. To avoid any “contamination” of physical health status by mental health status (and vice versa) [22], we used the physical and mental health subscales instead of the summary scales (which use items from both domains). Preliminary analyses of the eight SF-36 subscales at baseline found a correlation of 0.37 between the physical function and mental health subscales.

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The other six subscales had higher correlations with one or both of the physical or mental subscales (data not shown) and were not analyzed further. The correlations between the physical function and mental health subscales at each follow-up were similar to the baseline correlation, and the correlations between the change scores at any two consecutive time points were even lower (0.15–0.24). Thus, these two subscales measure two largely independent aspects of health status in this sample. 2.3.3. History of depression A history of depression at enrollment was defined as either a positive response to a question as to whether the patient had ever been told by a doctor that they were depressed, or a diagnosis of depression in the hospital chart during the 2 years before admission. 2.3.4. Antidepressant treatment Antidepressant medication prescriptions were abstracted from the prescription database for the period from 60 days before admission to the patient's last follow-up interview. 2.3.5. Cognitive impairment The Mini-Mental State Examination (MMSE) was administered at baseline and all follow-up interviews [23]; scores range from 30 (no impairment) to 0 (maximum impairment). 2.3.6. Premorbid disability Premorbid ADL disability (2 weeks before admission) was measured by self-report, using 14 items on a 3-point scale (completely independent, partially dependent and completely dependent) [24]. Patients with partial or complete dependence were considered disabled. Because almost all patients had some premorbid instrumental ADL disability, patients were classified into those with and without premorbid disability in basic (physical) ADL. 2.3.7. Medical illness at enrollment Four measures of medical illness were used. First, the Charlson Comorbidity Index was derived from chart review of diagnoses during the two years before enrollment [25]. Second, clinical severity of the medical illness was assessed at enrollment based on a global clinical impression on a scale ranging from 1 (not ill) to 9 (moribund) [26]. Third, the Acute Physiology Score (APS) derived from the Acute Physiology and Chronic Health Evaluation II was coded from the computerized laboratory test results and hospital chart data [27]. Fourth, the primary discharge diagnosis was abstracted from hospital administrative databases. 2.3.8. Social networks and support Social network and support questions administered at baseline and each follow-up interview included the perceived adequacy of emotional and tangible support (in the last month, could you have used more emotional support — or help with daily tasks — than you received?),

presence of a confidant (person you feel close and intimate with, share confidences with, can depend on); the number of children seen at least once a month, and the number of other relatives and friends seen at least once a month [28]. Bereavement was measured by a question about the death of someone close during the past year. 2.3.9. Sociodemographic and other variables Age, sex, years of education, marital status and living arrangement (alone or with others) were measured at enrollment. 2.4. Statistical methods The sample used for these analyses comprised enrolled patients with a baseline research interview and at least one follow-up interview at which both the SF-36 subscales were completed (more than 90% of the sample completed at least two of the follow-ups). We compared the baseline characteristics of the sample with two groups of excluded patients — those who died during the followup and those who were lost to follow-up for reasons other than death. Data were analyzed using the linear mixed model [29]; several correlation structures were examined and one was selected (compound symmetry) since it minimizes values of both the Akaike Information Criterion and the Bayesian Information Criterion. Two longitudinal outcomes were modeled separately: physical function and mental health as assessed by the SF-36 at 3, 6 and 12 months. The main independent variables of interest were depression (diagnosis and history) and social support, all measured at baseline. The potential confounders (also measured at baseline) include those described in Table 1. In the initial univariate models for each independent variable and confounder, the baseline score of the outcome and the time variable were included as covariates. Since the ratio of the sample size to the number of covariates was small (<8), we excluded from the final multivariate models those confounders with small absolute t values (<1). We tested interactions between depression diagnosis and follow-up time, depression diagnosis and history of depression and depression diagnosis and the social support variables. Antidepressant medication prescriptions at baseline and at follow-up were added to the final multivariate models, and interactions between medications and depression diagnosis were tested. Finally, a model with depression diagnosis as time-dependent covariate was fitted for both outcomes. Due to the relatively small number of tests we are interested in (effects of depression and social network on depression), we have not adjusted for multiple comparisons. Overall, 66% had complete data at the three follow-up times (3, 6 and 12 months); 25% had complete data at two follow-up times, and 9% had data at one follow-up time only. Missing data were imputed using the linear mixed model estimated on the available data. All

J. McCusker et al. / General Hospital Psychiatry 29 (2007) 340–348 Table 1 Baseline characteristics of study sample (n=210) Variables Sociodemographic Age Female Living at home alone Education (years) 1–6 7–12 >12 Depression Current diagnosis Major depression Minor depression No depression History of depression Use of antidepressant: at baseline During follow-up Physical health Primary discharge diagnosis Circulatory Respiratory Mental and nervous disorders Symptoms and signs Neoplasms Others Premorbid disability Acute Physiology Score (range, 0–11) Comorbidity (range, 0–8) Clinical severity (range, 1–7) Mini-Mental State Examination <24 <19 Social networks/support Confidant Bereavement Adequacy of tangible support a Adequacy of emotional support a No. of children seen every month No. of close friends/relatives seen every month b

n

Mean (S.D.) %

210 79.0 (7.3) 210 206 210

65.2 46.1 9.5 39.1 51.4

210 43.3 16.2 40.5 27.1 22.4 34.8

210 210 210 209

207 208 209 202 204

30.6 18.7 6.7 11.5 3.4 29.5 63.8 2.5 (2.3) 1.4 (1.5) 3.7 (1.0) 27.4 4.4

210 207 210 204 209 208

77.6 41.1 3.4 (1.0) 3.5 (1.0) 1.1 (1.4) 2.5 (2.6)

a Could have used: a lot more (1), some more (2), a little more (3) and no more (4) help. b 5=5–10 and 10=≥10.

the analyses were conducted with SAS software, Cary, NC, USA (version 9.1). 3. Results A total of 1718 patients met study eligibility criteria, and 1686 (98.0%) of these consented to depression screening (Fig. 1). The prevalence of depression (major or minor) was 27.9% (471/1686) at screening. Study participation rates were 73.0% (344/471) among patients with a depression diagnosis and 72.7% (186/256) in the sample of nondepressed patients invited to participate. Subsequently, 210 patients completed the baseline research interview and at least one follow-up, 145 patients died and the remainder (n=175) failed to complete either the

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baseline or any follow-up (including 20 patients who were interviewed but did not complete the SF-36 subscales). Most of this attrition took place between screening and the baseline research interview, reflecting difficulties in recontacting patients during their hospital stay. There were, however, no significant differences between the sample of 210 and the patients who were excluded for reasons other than death (n=175) in the screening diagnosis of depression, history of depression, SPMSQ score, age, sex or the chart-based measures of physical illness. In contrast, those who died were significantly more acutely ill and had higher comorbidity at baseline (data not shown). The baseline characteristics of the sample of analysis (n=210) are shown in Table 1. Fig. 2 shows the mean physical functioning SF-36 subscale scores (and 95% confidence intervals) at baseline and follow-up by depression diagnosis. Patients in all three groups had scores that remained significantly below the Canadian norms for these scales for comparable age groups [9]. However, a gradient in the scores was observed with the lowest scores among patients with major depression, followed by those with minor depression. Fig. 3 shows the same results for the mental health subscale. Patients with major depression had scores that remained substantially below the norms, patients with minor depression had scores approaching the norms, while those with no depression had scores similar to the norms. Table 2 shows the univariate and multivariate regression models (the covariates dropped from the multivariate models are those shown in the univariate but not the multivariate models shown in the table). The coefficient of a variable represents its population average effect on the SF-36 score over follow-up period (3–12 months). For example, for model B (physical function) patients with major depression had a follow-up score that was on average 9.2 points less than patients without depression. In comparison with patients with no depression diagnosis, those with major depression had significantly lower scores on both subscales at follow-up, even after adjustment for all covariates. There was no clinically or statistically significant effect of minor depression on either score. In multivariate analyses, other notable predictors of worse physical health status scores included less than 7 years of education, premorbid disability and presence of a confidant. Compared with the reference group of patients with “other” (miscellaneous) discharge diagnoses, a diagnosis of a respiratory, mental or nervous disorder was associated with a better physical function score at follow-up. Premorbid basic ADL disability and a lower Charlson comorbidity score predicted a worse mental health score at follow-up in multivariate analyses. In secondary analyses, we added depression diagnosis to the final multivariate model as time-dependent variables. The results differed for physical and mental health scales (data not shown). For physical health, the effect of major depression at baseline remained strong (−8.02, 96% CI −14.45 to −1.60), while diagnosis at follow-up was less

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Fig. 1. Enrollment flow chart.

strong (−3.71, 95% CI −7.77 to 0.35). In contrast, the measures of major depression at follow-up had a strong effect on mental health (−14.35, 95% CI −18.18 to −10.52) while the effect of the baseline diagnosis was much weaker (−.53, 95% CI −7.56 to 2.50). Minor depression at follow-up did not predict physical or mental health status.

Interactions between depression diagnosis and the social network/support variables were tested in the final multivariate models shown in Table 2. There were significant interactions only with the number of children seen every month (data not shown). Among patients with minor depression, both scores at follow-up improved with an increased number of children visiting (P=.002 for physical

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Fig. 2. Crude physical functioning scores over time (mean and 95% CI) by depression diagnosis.

function, P=.009 for mental health). Among patients with major depression, the mental health score at follow-up (but not the physical function score) was lower for those with more children visiting (P=.007). Finally, we added measures of antidepressant use at baseline and at follow-up to the final models (data not shown). Antidepressant use at baseline had a small negative effect upon mental health (but not physical health) at followup [−4.89 (95% CI −10.47 to 0.69)], with minimal changes in estimates of other variables in the model. Antidepressant use during the follow-up had no effect upon either mental health or physical health outcomes. There were no significant interactions between antidepressant use and depression diagnoses.

4. Interpretation This observational 12-month prospective study found that major depression in a sample of older medical inpatients is an important independent predictor of poorer physical and mental health status after discharge, even after adjustment for baseline disability, the nature and severity of physical illness

and other patient characteristics. Neither minor depression nor a history of depression predicted physical or mental health status scores at follow-up, either in univariate or multivariate analyses. The results of this study contribute to the literature in several ways. This is the first study of older medical inpatients with follow-up to 12 months to investigate the effect of depression diagnoses on both physical and mental aspects of health status measured with a widely used generic health status instrument. The results indicate that, even in a medically ill population, a diagnosis of major depression has a sustained, independent effect on both physical and mental health outcomes. However, there are important differences in the way major depression affects the two different outcomes. First, the mental health status scale (measuring a construct similar to that of depression) was strongly related to the diagnosis of major depression at the same point in time. This supports the use of this short (four-item) scale for the monitoring of treatment in major depression, as suggested previously [10]. Second, major depression at baseline predicted mental health status at follow-up, indicating the persistent nature of major depression in this population [30]. In contrast, the effect

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Table 2 Longitudinal multiple regression models a of baseline predictors of mental and physical subscales over 12 months Predictor

Physical function A

b

Estimate Baseline score of outcome 0.65 ⁎⁎ Follow-up time (months) −0.34 ⁎ Depression Current diagnosis Major depression (vs. no) −5.51 Minor depression (vs. no) −2.37 History of depression 2.50 Demographic Age −0.47 ⁎ Female (vs. male) −5.84 ⁎ <7 years education (vs. ≥7) −9.70 ⁎ Living at home alone 3.84 General health Primary discharge diagnosis Circulatory (vs. others) 1.67 Respiratory (vs. others) 8.01 Mental and nervous disorders 10.46 (vs. others) Symptoms and signs (vs. others) 6.88 Neoplasms (vs. others) −0.37 Comorbidity (continuous) −0.96 Clinical severity (continuous) −1.18 APS (continuous) −1.12 MMSE <24 −2.97 Premorbid disability −13.07 ⁎⁎ Social networks/support Bereavement −2.73 Confidant (vs. none) −7.54 ⁎ Adequacy of tangible support −0.93 Adequacy of emotional support −1.20 No. of friends visiting monthly −0.51 (continuous) No. of children visiting monthly 1.74 (continuous)

Mental health c

Ab

B (n=202) 95% CI

Estimate

95% CI

Estimate

B c (n=205) 95% CI

0.49 ⁎⁎ 0.41–0.57 −0.08 −0.43 to 0.28

Estimate

0.56–0.75 −0.68 to 0.01

0.54 ⁎⁎ 0.43–0.65 −0.35 ⁎ −0.68 to −0.02

−11.68 0.67 −10.33 to 5.61 −3.75 to 8.75

−9.22 ⁎⁎ −15.52 to −2.93 −8.29 ⁎⁎ −13.69 to −2.88 −6.28 ⁎ −3.94 −11.56 to 3.68 −2.85 −9.35 to 3.65 −1.76 2.96 −3.32 to 9.23 −4.72 −9.80 to 0.36 −3.06

−0.84 to −0.10 −0.26 −11.68 to −0.01 −4.20 −18.89 to −0.51 −11.56 ⁎ −1.63 to 9.31

−0.63 to 0.10 −0.20 −9.93 to 1.54 −4.02 −20.32 to −2.80 −4.28 −0.27

−0.49 to 0.09 −8.41 to 0.37 −11.58 to 3.01 −4.62 to 3.96

−5.23 to 8.56 −0.35 to 16.37 −0.86 to 21.78

−3.60 to 9.37 0.73–16.41 0.51–22.57

−3.66 to 7.21 −6.36 to 6.50 −10.70 to 7.21

2.89 8.57 ⁎ 11.54 ⁎

−2.50 to 16.26 9.60 ⁎ −15.85 to 15.10 1.09 −2.72 to 0.81 −1.35 −3.97 to 1.61 −2.28 to 0.04 −9.14 to 3.21 −19.39 to −6.74 −10.58 ⁎⁎ −8.33 to 2.87 −13.97 to −1.11 −3.61 to 1.75 −3.93 to 1.53 −1.64 to 0.62 −0.23 to 3.71

−2.23 4.79 1.72 ⁎ 0.78 0.33 0.01 −16.90 to −4.25 −6.90 ⁎⁎ 0.77–18.43 −13.59 to 15.78 −3.06 to 0.35

−0.17 −1.93 −3.68

−9.72 to 5.27 −7.40 to 16.99 0.36–3.07 1.52 ⁎ −1.38 to 2.93 −0.57 to 1.22 −4.78 to 4.80 −11.36 to −2.45 −5.43 ⁎

−11.76 to −0.79 −8.16 to 4.63 −8.15 to 2.04 −0.46 to 0.12 −6.37 to 2.50 −10.73 to 3.37

0.18–2.86

−10.02 to −0.84

−6.12 to 2.28 −2.99 to 7.15 −0.55 to 3.64 −1.09 to 3.26 −0.52 to 1.22

1.15

−0.93 to 3.22

−1.68 to 0.49

−1.92 2.08 1.55 1.08 0.35

0.30 to 4.15

−0.58

−2.04 to 0.89

−0.54

−1.97 to 0.88

−6.34 ⁎ −1.51

−12.66 to −0.02 −4.13 to 1.11

−0.59 2.23 ⁎

1.78 0.07 −1.74

95% CI

0.37 ⁎⁎ 0.28–0.47 −0.10 −0.45 to 0.26

a

Mixed linear model with correlation structure (compound symmetry). Model for each predictor variable, adjusted with time and baseline outcome score (sample sizes given in Table 1). c Final multivariate model. ⁎ P<.05. ⁎⁎ P<.01. b

of major depression at baseline on physical health status at follow-up was stronger than that of a diagnosis made at follow-up. In this population, patients with major depression at hospital admission had the worst physical health (compared to those with minor or no depression), and their health did not improve at follow-up (Fig. 1). Analysis of survival during follow-up in this same cohort found that, after adjustment for physical health and other covariates at hospital admission, patients with major depression did not have worse survival [14]. Thus, the main independent health impact of a diagnosis of major depression in older medical inpatients appears to be on morbidity rather than mortality. Visits from children appeared to reduce the negative effects of minor depression on both physical and mental

aspects of health status, as expected. In contrast, patients with major depression who reported more visits from children experienced worse physical health status at follow-up; visits by children among these more severely depressed patients may be a marker of greater need. The study has four main limitations. First, the most severely physically ill patients, those with moderate or severe cognitive impairment and patients who died during follow-up were excluded, so the study results are not generalizable to these groups of patients. Second, there was relatively high attrition (particularly between screening and the baseline interview, due to difficulties in recontacting patients during their hospital stay). However, the baseline characteristics of patients in the study sample (n=210) were similar to those of patients who failed to complete both the

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Fig. 3. Crude mental health scores over time (mean and 95% CI) by depression diagnosis.

baseline and at least one follow-up interview for reasons other than death (n=175). Third, the relatively small sample of patients with minor depression reduced the power of the study to detect effects of this diagnosis on the outcome. Fourth, our measures of antidepressant use were crude; data on the duration and dosages of antidepressants and on compliance are needed to evaluate whether use of these medications has an impact on health status. We conclude that, among older medical inpatients, major depression has a sustained negative effect on both physical and mental dimensions of health status, independent of the negative effects of physical health, premorbid disability and other covariates. These results underline the need for effective interventions for major depression in older medical inpatients. Major depression in older adults can respond to antidepressant and psychological treatments [31] and to disease management programs in primary care settings [32,33]. However, efforts to detect and treat major depression systematically in older medical inpatients have had disappointing results, in part because of high rates of patient attrition and poor adherence [18].

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