Open Access
Open Peer Review

This article has Open Peer Review reports available.

How does Open Peer Review work?

Association between subjective memory complaints and health care utilisation: a three-year follow up

BMC Geriatrics20099:43

DOI: 10.1186/1471-2318-9-43

Received: 20 April 2009

Accepted: 23 September 2009

Published: 23 September 2009

Abstract

Background

Subjective memory complaints (SMC) are common among elderly patients and little is know about the association between SMC and health care utilisation. Thus, the aim of this study was to investigate health care utilisation during a three-year follow-up among elderly patients consulting their general practitioner and reporting subjective memory complaints (SMC).

Methods

This study was conducted as a prospective cohort survey in general practice with three-year follow-up. Selected health care utilisation or costs relative to SMC adjusted for potential confounders were analyzed in a two-part model where the incidence of use of a selected health care service were analyzed separately from the quantity of use for those that use the service. The former analyzed in a Poisson regression approach, the latter in a generalized linear regression model.

Results

A total 758 non-nursing home residents aged 65 years and older consulted their GP in October and November 2002 and participated in the present study. The adjusted probability of nursing home placement was significantly increased in subjects with SMC relative to subjects without SMC (RR = 2.3). More generally, SMC was associated with an increase in the cost of selected health care utilisation of 60% over three years (p = 0.003).

Conclusion

The data of this study indicated that in an elderly primary care population the presence of SMC increased the cost of health care utilisation by 60% over three years. Thus, inquiry into SMC may contribute to a risk profile assessment of elderly patients and may identify patients with an increased use of health care services.

Background

In studies of older patients, the reported prevalence of subjective memory complaints (SMC) shows a huge variation with figures ranging from 10-56% [1, 2]. The large variation may be explained by sample selection or by the methods applied for assessing SMC [1]. Studies have consistently associated SMC with depression [24], as well as personality traits [5], high age, low education and female gender [1]. A Danish study indicated that these patients rarely share their perception of SMC with their General Practitioner (GP) spontaneously [6], even though SMC may identify frail patients and inquiry into SMC may easily be implemented in a busy GP routine consultation.

In some studies, association has been found between memory complaints and cognitive impairment on testing, even after adjustment for depressive symptoms [7, 8]. However, longitudinal studies assessing the value of SMC in predicting dementia or cognitive decline have shown varying results [916]. Thus, the nature of SMC is complex [17].

In a study from 1999 among 8775 non-institutionalized persons aged 65 or more, a single question about health strongly predicted subsequent health care utilisation after a year [18]. Other research suggests that patients with mental health conditions use general medical services at a higher rate than those without mental health conditions [1921]. Furthermore, dementia has been associated with increased health care utilisation in several studies [22, 23]. In our recent study, SMC was associated with an increased probability for nursing home placement over 4 years following the assessment [24]. However, we did not identify any other studies addressing the association between the presence of SMC and health care utilisation. Thus, the aim of the present prospective study was to investigate health care utilisation during a three-year follow-up among elderly patients with and without SMC consulting their general practitioner.

Methods

Study Population

All 17 practices comprising a total of 24 GPs in the central district of the municipality of Copenhagen, Denmark, participated in this study. A total of 40.865 patients were listed and 2.934 were 65 or older. Patients' aged 65 and older consulting their GP, regardless of reason for the encounter, were asked to participate in the study and received information both verbally and written. All participants signed an informed consent declaration and were not offered a refund. Patients not able to speak or read Danish, patients living in a nursing home, and patients with severe acute or terminal illness, or specialist-diagnosed patients with dementia were excluded. Non-participants were defined as those who were not excluded because of the exclusion criteria, but refused to participate. The participants were enrolled during October and November 2002.

Outcome

End-point variables were GP related contacts, out-of-hour services, hospitalization and nursing home placement within a three-year period from enrolment, and a cumulated value of these services.

Measurements

In brief, the examination contained:
  1. 1)

    A self-administered participant questionnaire concerning aspects of memory and sociodemographics. Information on SMC was obtained from the following item: "How would you judge your memory?" Theresponse categories were: "excellent", "good", "less good", "poor", or "miserable". Patients rating their memory as "less good", "poor" or "miserable" were classified as patients with SMC, while patients rating their memory as "excellent" or "good" were defined as patients without SMC.

     
  2. 2)

    A self-administered quality of life assessment. The patients completed the Danish Validated Version of Euro-Qol-5D. Euro-Qol-5D is a standardised instrument for use as a measure of health outcome and measures five dimensions - mobility, self-care, usual activities, pain/discomfort, and anxiety/depression - each by three levels of severity [25]. The anxiety/depression dimension was used as a proxy for depression.

     
  3. 3)

    A GP- or nurse- administered Mini Mental State Exermination (MMSE). The MMSE, a widely distributed test recommended in GP guidelines as a cognitive screening test, was completed after the completion of the GP questionnaire [26]. The MMSE score ranges from 0-30; a score lower than 24 was taken as indicative of cognitive impairment.

     

Registry data

In Denmark, much health information is collected in national registers based on a unique personal identification number allocated to each inhabitant [27]. Information concerning incident deaths, hospital contacts and GP consultations were retrieved from the central national databases by the statistical department of the Danish National Board of Health at the end of 2007. The municipality of Copenhagen provided information concerning nursing home placement at the end of 2006.

In this study the following outcomes were investigated in the three-year period from January 1st 2003 until 31st December 2005:
  1. 1)

    Practice consultations (number of consultations)

     
  2. 2)

    Home visit consultations by GP (number of visits)

     
  3. 3)

    GP out-of-hours contacts (number of contacts)

     
  4. 4)

    Hospital admission (days in hospital, not as out-patient)

     
  5. 5)

    Out-patient stay (days in outpatient clinic)

     
  6. 6)

    Emergency room consultations (number of visits)

     
  7. 7)

    Nursing home placement (days in institution).

     
Health care utilisation was defined as the sum of the number of services or time (days) of stay over the three-year follow-up period; or a valuation based on the prices in Table 1. For those, who had died (and thereby did not use health care services during all three years), the nominal outcome was multiplied with the inverse of the proportion of the three years the subject was alive. Annualized outcomes were constructed by dividing the three-year outcomes by three.
Table 1

Valuation of selected health care services

Service

Unit

Value1

Source

Practice consultations

1 consultation

€ 14,39

Danish health insurance register (SSR)

Visits by GP

1 visit

€ 23,81

Danish health insurance register (SSR)

Hospital stay (not as outpatient)

1 admission day

€ 470,84

Journal of the Danish Medical Association 2005; 167 (07): 807

Outpatient stay

1 admission day

€ 187,39

The National Board of Health (drg.dk)

Out-of-hours contacts

1 contact

€ 14,66

Danish health insurance register (SSR)

Emergency

1 visit

€ 105,74

The National Board of Health (drg.dk)

Nursing home

1 admission day

€ 127,80

Journal of the Danish Medical Association 2005; 167 (07): 807

12004 prices in DKK converted to EUR using the july 1st 2004 spot rate DKK743.35 = EUR100 (source: Danish national bank http://www.nationalbanken.dk)

Statistical analysis

Differences in characteristics and health care utilisation between participants with and without SMC were tested by chi-squared tests. A total cost for the health care utilisation was calculated using the valuation in Table 1; the difference in this cost between participants with and without SMC was analyzed with a Kruskal-Wallis non-parametric test. Differences in total cost between subgroups of the participants were tested by the F-test of the regression parameter(s) corresponding to the characteristic classifying the subgroups in a linear regression on total cost, additionally adjusted for SMC. These tests evaluated the effect of the characteristic on the total cost beyond the part of the effect that was mediated by SMC.

Multivariate analysis of health care utilisation followed a two-part model where the incidence of use (ever used) of a selected health care service was analyzed separately from the quantity of use for those that use the service [28]. The incidence was analyzed in a Poisson regression approach [29] so that the regression parameters were equivalent to the log of the relative risk (RR) of using the service ever in the study period. For the participants that use the service (or have cost>0) the quantity of use was analyzed in a generalized linear model using a Gamma distribution and a logarithmic link function; the parameters from this model were interpreted as the log of a (multiplicative) factor how much more the service was used compared to a baseline class. A combined (multiplicative) effect of having SMC compared to not having SMC was straightforwardly calculated by multiplying the RR from the first part and the factor from the second part. Statistical significance was assessed at a 5% level. We adjusted for multiple testing by the method of Benjamini-Hochberg in the final multivariate analysis [30].

Ethics

The Scientific Ethical Committee for Copenhagen and Frederiksberg Municipalities evaluated the project. The Danish Data Protection Agency, the Danish College of General Practitioners Study Committee as well as The National Board of Health approved the project.

Results

The final cohort consisted of 775 non-nursing home residents of which 758 filled out the SMC item. Figure 1 shows the trial flow. The average age of participants at baseline was 74.8 of whom 38.6% were males; average MMSE was 28.2 (range: 16-30). According to our definition 177 (23%) had SMC at baseline. Non-participants were more likely to be males (OR = 1.4) and were, according to the GP, less likely to complain about memory problems, (OR = 1.8). All participants were followed up until the end of 2005 and none were lost to follow-up.
https://static-content.springer.com/image/art%3A10.1186%2F1471-2318-9-43/MediaObjects/12877_2009_Article_173_Fig1_HTML.jpg
Figure 1

Flowchart of Study population.

During the study period 88 (11.6%) died and 50 (6.6%) were admitted to nursing homes. A total of 701 (92.5%) had at least one GP consultation and 432 (60.0%) have at least one hospital admission during the study period. Furthermore, SMC is not seen to correlate with MMSE (Table 2). Valuations of selected health care services are shown in Table 1.
Table 2

Baseline characteristics and health care utilisation of the study participants (n = 758) by Subjective Memory Complaints (SMC)

  

SMC

  
  

No

(n = 581)

Yes

(n = 177)

  
  

n

%

n

%

Sign.

Missing

Death

no

517

89,0

153

86,4

  
 

yes

64

11,0

24

13,6

  

MMSE

≥ 24

555

95,5

165

93,2

  
 

< 24

26

4,5

12

6,8

  

Age

60 - 74

318

54,7

86

48,6

  
 

75 - 84

207

35,6

68

38,4

  
 

85+

56

9,6

23

13,0

  

Sex

male

233

40,1

61

34,5

  
 

female

348

59,9

116

65,5

  

Living without partner

no

240

41,4

60

34,3

 

3

 

yes

340

58,6

115

65,7

  

Education

< 8 years

226

38,9

69

39,0

  
 

> 8 years

355

61,1

108

61,0

  

Home care

no

473

81,7

126

72,0

***

4

 

yes

106

18,3

49

28,0

  

Mobility1

no problems

384

67,3

90

52,0

***

14

 

some problems

187

32,7

83

48,0

  

Self-care1

no problems

539

94,7

158

90,8

 

15

 

some problems

30

5,3

16

9,2

  

Usual activities1

no problems

412

72,5

84

48,6

  
 

some problems

145

25,5

84

48,6

***

17

 

severe problems

11

1,9

5

2,9

  

Pain/discomfort1

no

216

38,4

45

25,9

  
 

moderate

323

57,4

111

63,8

***

21

 

extreme

24

4,3

18

10,3

  

Anxiety/depression1

no

442

77,8

98

57,0

  
 

moderate

115

20,2

71

41,3

***

18

 

extreme

11

1,9

3

1,7

  

Health Care Utilization

Practice consultations2

no

41

7,1

16

9,0

  
 

yes

540

92,9

161

91,0

  

Visits by GP2

no

422

72,6

117

66,1

  
 

yes

159

27,4

60

33,9

  

Hospital stay (no outpatient)2

no

259

44,6

67

37,9

  
 

yes

322

55,4

110

62,1

  

Outpatient stay2

no

165

28,4

34

19,2

*

 
 

yes

416

71,6

143

80,8

  

Out-of-hours contact2

no

548

94,3

170

96,0

  
 

yes

33

5,7

7

4,0

  

Emergency2

no

345

59,4

82

46,3

**

 
 

yes

236

40,6

95

53,7

  

Nursing home2

no

554

95,4

154

87,0

***

 
 

yes

27

4,6

23

13,0

  

* significant at 5% level ** significant at 1% level *** significant at 0.1% level, 1based on Euro-Qol-5D, for mobility and self-care the third category did not appear because of the method of data collection, 2incidence in the period 2003-2005.

Annualized cost (in EUR) of health care utilisation by SMC and participant characteristics is shown in Table 3. Lower MMSE scores, increased age, lower education, home care and lower physical activity increased the cost of health care utilisation. The differences in health care utilisation and costs attributable to SMC, i.e. adjusted for the characteristics listed in Table 3, are shown in Table 4. The presence of SMC significantly increased the probability of nursing home placement (RR = 2.3). More generally, SMC was significantly associated with an increase in health care costs for the combined selected services over the three years of follow-up by 60%. When the cost of nursing home admission is omitted from the total cost analysis, SMC is associated only with a non-significant 23% increase
Table 3

Annualised cost (EUR) of health care utilisation by Subjective Memory Complaints (SMC) and participant characteristics

  

SMC

 
  

No (n = 581)

Yes (n = 177)

 
  

Median

IQR

Median

IQR

Sign.1

Total cost (EUR)

 

838

192

3389

1577

597

9894

***2

MMSE

≥24

831

192

3209

1457

548

7620

**

 

< 24

4572

183

13033

9888

2597

22082

 

Age

60 - 74

566

178

2170

993

274

1659

 
 

75 - 84

1143

226

4438

3321

1076

14743

***

 

85+

3277

494

24366

14609

1713

27545

 

Sex

male

1036

202

3637

1190

322

3302

 
 

female

794

187

3360

2187

733

13738

 

Living without partner

no

815

154

2601

1225

541

4135

 
 

yes

842

219

3931

2125

695

14770

 

Education

< 8 years

944

185

4151

2998

528

17280

*

 

> 8 years

831

197

2750

1383

612

6291

 

Home care

no

660

182

2551

1069

307

2998

***

 

yes

2642

682

9065

14609

3329

23801

 

Mobility

no problems

613

163

2327

1177

280

4985

***

 

some problems

1778

313

8509

2883

958

14770

 

Self-care

no problems

832

192

3294

1431

548

6755

**

 

some problems

2027

288

8896

13416

2788

20493

 

Usual activities

no problems

605

163

2380

1194

301

4160

 
 

some problems

1891

433

6497

2556

767

13791

 
 

severe problems

1531

178

14788

3615

3248

23152

***

Pain/discomfort

no

594

133

2227

1811

695

14609

 
 

moderate

1063

222

4266

1510

543

6161

 
 

extreme

1877

324

6137

2669

1050

12867

 

Anxiety/depression

no

794

187

3182

1494

548

8905

 
 

moderate

1036

226

3595

1577

682

9894

 
 

extreme

13606

887

17944

12512

7620

30547

 

*significant at 5% level ** significant at 1% level *** significant at 0.1% level

1Significance of the regression parameter of the corresponding participant characteristic in a linear regression on total cost, adjusted for SMC

2Wilcoxon non-parametric test

Table 4

Selected health care utilisation and costs in subjects with Subjective Memory Complaints (SMC) relative to patients without SMC1

 

The RR of any use of the corresponding service at all

Factor how much more people with SMC use the service

Combined effect

Service

RR

95% CI

p-value2

Factor

95% CI

p-value2

 

GP contacts

         

Practice consultations

0,976

0,922

1,032

0,3924

0,988

0,866

1,126

0,8559

0,964

Visits by GP

1,116

0,876

1,421

0,3863

0,967

0,717

1,304

0,8255

1,079

GP contacts (cost)

0,970

0,920

1,023

0,2610

1,001

0,883

1,135

0,9830

0,972

Hospital stay

         

Hospital stay (not as outpatient, days)

1,052

0,911

1,216

0,4953

1,189

0,895

1,582

0,2282

1,252

Outpatient stay (days)

1,111

1,010

1,221

0,0344

1,082

0,875

1,338

0,4663

1,202

Hospital stay (cost)

1,061

0,978

1,151

0,1611

1,178

0,920

1,509

0,1896

1,250

Out-of-hours services

         

Out-of-hours GP contacts

0,575

0,237

1,398

0,1686

1,437

1,092

1,891

0,0116

0,827

Emergency (visits)

1,209

1,007

1,452

0,0512

1,073

0,916

1,256

0,3828

1,297

Out-of-hours services (cost)

1,121

0,939

1,340

0,2183

1,172

0,977

1,405

0,0858

1,314

Nursing home

         

Nursing home (days)

2,296

1,357

3,886

0,0075

0,922

0,686

1,238

0,5900

2,117

Nursing home (cost)

2,296

1,357

3,886

0,0075

0,922

0,686

1,238

0,5900

2,117

The above combined (cost)

0,990

0,961

1,020

0,5070

1,615

1,234

2,114

0,0003

1,599

1All analyses adjusted for the participant characteristics presented in Table 3

2Due to multiple testing the level of significance is set to 0.0081

Discussion

To our knowledge, this is the first study to demonstrate that in elderly patients SMC was attributable to an increase in cost by 60% over three years for selected health care services. Specifically, SMC increased the probability of nursing home placement. Much of the excess cost in the SMC group seems to be explained by the higher frequency of nursing home admission.

SMC is a commonly reported symptom in the elderly [1, 2]. In this study we adjusted for commonly known confounders e.g. depression and cognitive performance, and the result indicated that the increase in health care utilisation attributed to SMC was substantial. The tendency, that nursing home placement was increased has been reported previously using data from this study. The increased health care utilisation may not solely be explained by nursing home admission. Tendencies of increased use of out-patient clinic admissions and out-of-hour services can be observed. In contrast, the use of GP daytime consultations and acute hospital admittance were not increased.

The reported effect of SMC was beyond various other potential confounders. It is well-known that the presence of dementia in general is associated with an increased health care utilisation [31]. This is in accordance with this study, where our item indicating that significant cognitive impairment (defined as MMSE less than 24) was an independent predictor for nursing home placement. Also, depression in old age has also consistently been associated with an increased health care costs, even after controlling for chronic medical co-morbidity [32]. Our study found that age, but not depressive symptoms were associated with an increased health care utilisation. Furthermore, low education increased health care utilisation. The absence of correlation between SMC and cognitive functioning (MMSE) stresses their different psychometric properties. We assume that SMC measures a global functioning in elderly patients. In Table 2 it can be seen that there is no notable difference in mortality between the subjects with and without SMC. Hence, the difference in health care utilisation and costs cannot be attributed to the high end-of-life utilisation and costs that are generally observed.

The mechanism by which SMC leads to increased health care utilisation is, in our view, not a direct causative relation. However, we see a statistical association between SMC and health care utilisation as residual confounding, i.e. there are certain factors - possibly unknown or immeasurable - beyond the covariates that are used in the analyses, that cause the subject to have memory complaints and cause increased health care utilisation.

The sampling of the participants reflects the population in which the GP has an opportunity to ask questions about SMC. Thus, we deliberately designed the study to include a patient sample, which reflects daily clinical practice. The nation-wide databases used in order to evaluate our main outcomes are regarded as highly valid. Thus, we believe that our findings are valid.

The statistical analysis was done in a two-part model according to recommendations [28]. Data tend to conform to the analytic assumptions for these models, and the models can be used to gain insight in the process of health care utilisation. The decision to have any use at all of a certain service is most likely made by the person and so is related primarily to personal characteristics, while the cost and frequency per user may be more related to characteristics of the health care system.

Several limitations must be addressed. This study had some selection biases at baseline, which may decrease generalizability. Only elderly persons who consulted their GP for whatever reason were included, and they may be more vulnerable than elderly persons in the general population. We did not have access to databases regarding medication, which would have been relevant to evaluate. Likewise, we did not obtain information about medical diagnosis in the participants, as diagnostic criteria are not systematically implemented in general practice in Denmark, and we wanted the study to reflect current standards. Participants who had already been diagnosed with dementia by a specialist were excluded from the study, which is reflected by the high average MMSE in our study population. A MMSE score less than 24 has been widely used as an indication of the presence of cognitive impairment in population based studies [33]. However, epidemiological research has shown that MMSE scores are affected by age, education, and cultural background [33] and MMSE is not sufficient to diagnose dementia. In our study we used the depression item in the Euro-Qol-5D to identify patients with self reported anxiety and depression. These patients may not fulfill international criteria for anxiety and depression. However, this item may serve as indicator for affective symptoms.

There is a lack of consensus concerning the assessment of SMC. Some studies have assessed the presence of SMC by a single item, others by several items. In this study, a single item was used to assess SMC. This item did not allow us to know whether the patient was calibrating the response by comparing to former functioning or to the functioning of others. Notably, our SMC item did not distinguish between short-term and long-term memory loss. We recommend that future studies give more attention to this specific aspect and also include informant reports on memory.

Conclusion

The data suggest that in an elderly primary care population SMC is associated with an increased health care utilisation by 60%, primarily because of increased nursing home placement. Therefore, the result of this study indicates that GPs may identify elderly patients with an increased probability of subsequent health care utilisation by routinely inquiring about memory problems.

Declarations

Acknowledgements

This work was supported by a General Practitioners' Foundation for Education and Development Grant (Grant nr: R56-A369-B186). The sponsor did not contribute to any part of the study or the preparation of the manuscript.

Authors’ Affiliations

(1)
Section and Research Unit of General Practice, Institute of Public Health, University of Copenhagen
(2)
Memory Disorders Research Group, Department of Neurology, Rigshospitalet, Copenhagen University Hospital

References

  1. Jonker C, Geerlings MI, Schmand B: Are memory complaints predictive for dementia? A review of clinical and population-based studies. Int J Geriatr Psychiatry. 2000, 15: 983-991. 10.1002/1099-1166(200011)15:11<983::AID-GPS238>3.0.CO;2-5.View ArticlePubMedGoogle Scholar
  2. Jungwirth S, Fischer P, Weissgram S, Kirchmeyr W, Bauer P, Tragl KH: Subjective memory complaints and objective memory impairment in the Vienna-Transdanube aging community. J Am Geriatr Soc. 2004, 52: 263-268. 10.1111/j.1532-5415.2004.52066.x.View ArticlePubMedGoogle Scholar
  3. Bassett SS, Folstein MF: Memory complaint, memory performance, and psychiatric diagnosis: a community study. J Geriatr Psychiatry Neurol. 1993, 6: 105-111.View ArticlePubMedGoogle Scholar
  4. Kahn RL, Zarit SH, Hilbert NM, Niederehe G: Memory complaint and impairment in the aged. The effect of depression and altered brain function. Arch Gen Psychiatry. 1975, 32: 1569-1573.View ArticlePubMedGoogle Scholar
  5. Hanninen T, Reinikainen KJ, Helkala EL, Koivisto K, Mykkanen L, Laakso M, Pyorala K, Riekkinen PJ: Subjective memory complaints and personality traits in normal elderly subjects. J Am Geriatr Soc. 1994, 42: 1-4.View ArticlePubMedGoogle Scholar
  6. Waldorff FB, Rishoj S, Waldemar G: If you don't ask (about memory), they probably won't tell. J Fam Pract. 2008, 57: 41-44.PubMedGoogle Scholar
  7. Gagnon M, Dartigues JF, Mazaux JM, Dequae L, Letenneur L, Giroire JM, Barberger-Gateau P: Self-reported memory complaints and memory performance in elderly French community residents: results of the PAQUID Research Program. Neuroepidemiology. 1994, 13: 145-154. 10.1159/000110373.View ArticlePubMedGoogle Scholar
  8. Jonker C, Launer LJ, Hooijer C, Lindeboom J: Memory complaints and memory impairment in older individuals. J Am Geriatr Soc. 1996, 44: 44-49.View ArticlePubMedGoogle Scholar
  9. Schmand B, Jonker C, Geerlings MI, Lindeboom J: Subjective memory complaints in the elderly: depressive symptoms and future dementia. Br J Psychiatry. 1997, 171: 373-376. 10.1192/bjp.171.4.373.View ArticlePubMedGoogle Scholar
  10. Schofield PW, Marder K, Dooneief G, Jacobs DM, Sano M, Stern Y: Association of subjective memory complaints with subsequent cognitive decline in community-dwelling elderly individuals with baseline cognitive impairment. Am J Psychiatry. 1997, 154: 609-615.View ArticlePubMedGoogle Scholar
  11. Wang L, van BG, Crane PK, Kukull WA, Bowen JD, McCormick WC, Larson EB: Subjective memory deterioration and future dementia in people aged 65 and older. J Am Geriatr Soc. 2004, 52: 2045-2051. 10.1111/j.1532-5415.2004.52568.x.View ArticlePubMedGoogle Scholar
  12. Jorm AF, Christensen H, Korten AE, Jacomb PA, Henderson AS: Memory complaints as a precursor of memory impairment in older people: a longitudinal analysis over 7-8 years. Psychol Med. 2001, 31: 441-449.PubMedGoogle Scholar
  13. Smith GE, Petersen RC, Ivnik RJ, Malec JF, Tangalos EG: Subjective memory complaints, psychological distress, and longitudinal change in objective memory performance. Psychol Aging. 1996, 11: 272-279. 10.1037/0882-7974.11.2.272.View ArticlePubMedGoogle Scholar
  14. Wang PN, Wang SJ, Fuh JL, Teng EL, Liu CY, Lin CH, Shyu HY, Lu SR, Chen CC, Liu HC: Subjective memory complaint in relation to cognitive performance and depression: a longitudinal study of a rural Chinese population. J Am Geriatr Soc. 2000, 48: 295-299.View ArticlePubMedGoogle Scholar
  15. Palmer K, Backman L, Winblad B, Fratiglioni L: Detection of Alzheimer's disease and dementia in the preclinical phase: population based cohort study. BMJ. 2003, 326: 245-10.1136/bmj.326.7383.245.View ArticlePubMedPubMed CentralGoogle Scholar
  16. Glodzik-Sobanska L, Reisberg B, De SS, Babb JS, Pirraglia E, Rich KE, Brys M, de Leon MJ: Subjective memory complaints: presence, severity and future outcome in normal older subjects. Dement Geriatr Cogn Disord. 2007, 24: 177-184. 10.1159/000105604.View ArticlePubMedGoogle Scholar
  17. Reid LM, Maclullich AM: Subjective memory complaints and cognitive impairment in older people. Dement Geriatr Cogn Disord. 2006, 22: 471-485. 10.1159/000096295.View ArticlePubMedGoogle Scholar
  18. Bierman AS, Bubolz TA, Fisher ES, Wasson JH: How well does a single question about health predict the financial health of Medicare managed care plans?. Eff Clin Pract. 1999, 2: 56-62.PubMedGoogle Scholar
  19. Fogarty CT, Sharma S, Chetty VK, Culpepper L: Mental health conditions are associated with increased health care utilization among urban family medicine patients. J Am Board Fam Med. 2008, 21: 398-407. 10.3122/jabfm.2008.05.070082.View ArticlePubMedGoogle Scholar
  20. Thomas MR, Waxmonsky JA, Gabow PA, Flanders-McGinnis G, Socherman R, Rost K: Prevalence of psychiatric disorders and costs of care among adult enrollees in a Medicaid HMO. Psychiatr Serv. 2005, 56: 1394-1401. 10.1176/appi.ps.56.11.1394.View ArticlePubMedGoogle Scholar
  21. Salsberry PJ, Chipps E, Kennedy C: Use of general medical services among Medicaid patients with severe and persistent mental illness. Psychiatr Serv. 2005, 56: 458-462. 10.1176/appi.ps.56.4.458.View ArticlePubMedGoogle Scholar
  22. Hill JW, Futterman R, Duttagupta S, Mastey V, Lloyd JR, Fillit H: Alzheimer's disease and related dementias increase costs of comorbidities in managed Medicare. Neurology. 2002, 58: 62-70.View ArticlePubMedGoogle Scholar
  23. Fillit H, Hill JW, Futterman R: Health care utilization and costs of Alzheimer's disease: the role of co-morbid conditions, disease stage, and pharmacotherapy. Fam Med. 2002, 34: 528-535.PubMedGoogle Scholar
  24. Waldorff FB, Siersma V, Waldemar G: Association between subjective memory complaints and nursing home placement: a four-year follow-up. Int J Geriatr Psychiatry. 2009, 24: 602-609. 10.1002/gps.2163.View ArticlePubMedGoogle Scholar
  25. Rabin R, de CF: EQ-5D: a measure of health status from the EuroQol Group. Ann Med. 2001, 33: 337-343. 10.3109/07853890109002087.View ArticlePubMedGoogle Scholar
  26. Folstein MF, Folstein SE, McHugh PR: "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975, 12: 189-198. 10.1016/0022-3956(75)90026-6.View ArticlePubMedGoogle Scholar
  27. Olivarius NF, Hollnagel H, Krasnik A, Pedersen PA, Thorsen H: The Danish National Health Service Register. A tool for primary health care research. Dan Med Bull. 1997, 44: 449-453.PubMedGoogle Scholar
  28. Diehr P, Yanez D, Ash A, Hornbrook M, Lin DY: Methods for analyzing health care utilization and costs. Annu Rev Public Health. 1999, 20: 125-144. 10.1146/annurev.publhealth.20.1.125.View ArticlePubMedGoogle Scholar
  29. Zou G: A modified poisson regression approach to prospective studies with binary data. Am J Epidemiol. 2004, 159: 702-706. 10.1093/aje/kwh090.View ArticlePubMedGoogle Scholar
  30. Benjamini Y, Hochberg Y: Controlling for the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society: Series B. 1995, 57: 289-300.Google Scholar
  31. Kronborg AC, Sogaard J, Hansen E, Kragh-Sorensen A, Hastrup L, Andersen J, Andersen K, Lolk A, Nielsen H, Kragh-Sorensen P: The cost of dementia in Denmark: the Odense Study. Dement Geriatr Cogn Disord. 1999, 10: 295-304. 10.1159/000017135.View ArticleGoogle Scholar
  32. Luppa M, Heinrich S, Matschinger H, Sandholzer H, Angermeyer MC, Konig HH, Riedel-Heller SG: Direct costs associated with depression in old age in Germany. J Affect Disord. 2008, 105: 195-204. 10.1016/j.jad.2007.05.008.View ArticlePubMedGoogle Scholar
  33. Tombaugh TN, McIntyre NJ: The mini-mental state examination: a comprehensive review. J Am Geriatr Soc. 1992, 40: 922-935.View ArticlePubMedGoogle Scholar
  34. Pre-publication history

    1. The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2318/9/43/prepub

Copyright

© Waldorff et al; licensee BioMed Central Ltd. 2009

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Advertisement