Open Access

Unmet health needs in patients with coronary heart disease: implications and potential for improvement in caring services

Health and Quality of Life Outcomes20031:26

https://doi.org/10.1186/1477-7525-1-26

Received: 10 June 2003

Accepted: 23 July 2003

Published: 23 July 2003

Abstract

Background

Improving the quality of health care services requires tailoring facilities to fulfil patients' needs. Satisfying patients' healthcare needs, listening to patients' opinions and building a closer provider-user partnership are central to the NHS. Few published studies have discussed cardiovascular patients' health needs, but they are not comprehensive and fail to explore the contribution of outcome to needs assessment.

Method

A comprehensive self-administered health needs assessment (HNA) questionnaire was developed for concomitant use with generic (Short Form-12 and EuroQOL) and specific (Seattle Angina Questionnaire) health-related quality of life (HRQL) instruments on 242 patients admitted to the Acute Cardiac Unit, Nottingham.

Results

38% reported difficulty accessing health facilities, 56% due to transport and 32% required a travelling companion. Mean HRQOL scores were lower in those living alone (P < 0.05) or who reported unsatisfactory accommodation. Dissatisfaction with transport affected patients' ease of access to healthcare facilities (P < 0.001). Younger patients (<65 y) were more likely to be socially isolated (P = 0.01). Women and patients with chronic disease were more likely to be concerned about housework (P < 0.05). Over 65 s (p < 0.05) of higher social classes (p < 0.01) and greater physical needs (p < 0.001) had more social needs, correlating moderately (0.32 < r < 0.63) with all HRQL domains except SAQ-AS. Several HRQL components were highly correlated with the HNA physical score (p < 0.001).

Conclusions

Patients wanted more social (suitable accommodation, companionship, social visits) and physical (help aids, access to healthcare services, house work) support. The construct validity and intra-class reliability of the HNA tool were confirmed. Our results indicate a gap between patients' health needs and available services, highlighting potential areas for improvement in the quality of services.

Keywords

Health needs assessmentHealth-related quality of lifeQuality of service.

Introduction

Medical professionals tend to focus on a medical model of health care. This ignores the more comprehensive approach which addresses 'the state of physical, mental and social well being'. Defining health needs is difficult, so it is not surprising that numerous definitions have been proposed in the past. Classifying needs in a sociologic environment as 'normative', felt', expressed', and 'comparative', remains one of the best, [1] despite its ignoring cost-effectiveness as a major determinant of healthcare provision. 'Ability to benefit from health care services' is a definition of 'needs'.[2] which minimises the role of lay individuals, focusing on 'health care' rather than 'health' [3] and is constrained by existing healthcare facilities. Additionally, benefit from healthcare may be affected inversely by the severity of disease.[4]

Geographic variations, socio-economic status and the knowledge base and attitude of the population may influence demand for health care, while medical guidelines and effectiveness of interventions may affect health care availability. Ideally, the provision of health care services should meet most of the populations' needs but these may not be constant, so health needs assessment (HNA) surveys are necessary both locally and nation-wide to establish what services are required to match these needs.

'Health needs' and 'healthcare needs'

'Health' covers a wide range of issues so 'health needs' ought to include at least social care, accommodation, health care, finance, education, employment, leisure and transport. Even social facilities such as a bus service to reach health services, road safety regulations, clean air policies and occupational health fall under the health need banner. It is not possible to attain a state of full health in every instance, so the goal of healthcare needs is optimal state of health. Nevertheless, if primary care aims to improve health as well as prove health services, these factors should be identified as health-related issues and referred to other sectors for action. [5]

Advantages of health needs assessment

HNA as a key point in health system involves both public and professional in the decision-making process, increases service utilisation rates, provides a reliable platform on which to base decisions regarding the withdrawal of unnecessary services and has the potential to inform priority setting and primary care planning. [6]

HNA in patients with CAD

It is essential to consider patients' health care needs as determined by epidemiological, comparative and corporate approaches [7]; investigating patients perceptions; the cost-effectiveness of interventions; and the potential risks of not offering services for patients with coronary artery disease (CAD) such as increased hospitalisation, morbidity and mortality [8]. Results from other studies emphasise that offering care for patients with progressive cardiac illnesses is not currently based on their needs.[9]

The contribution of quality of life to HNA

Generic measures are necessary to provide an overview of current health status, to compare results among different populations with diverse socio-economic backgrounds, to compare interventions and to supply quantitative data for economic evaluation. [10] In patients with co-morbid illness, generic measures have considerable merit. Disease-specific measures however can detect subtle changes due to interventions, are sensitive to the disorder under investigation and may be more likely than generic tools to reflect clinical changes in that disorder. Consequently it is generally recommended that both generic and disease specific instruments are applied to cover all aspects of health-related quality of life. [1114]

Method of study

General considerations

This descriptive cross-sectional study appraises the health needs of cardiac patients admitted to a coronary care unit following two qualitative and quantitative pilot studies. Overall 242 out of 260 patients (93%) who consented to participate in the survey returned the completed questionnaires after two reminders. All had symptoms suggestive for a myocardial infarction, diagnosed clinically based on the Nottingham Heart Attack Register guidelines. [15]

Method of administration

In the absence of an available tool for healthcare needs assessment of patients with CAD, we developed our own questionnaire, the Nottingham Health Needs Assessment (NHNA). The NHNA questionnaire was developed after a rigorous review of the literature, expert views, discussions with medical staff and patients and information compiled at patient interview. The NHNA covers demographic data, employment, mobility and transport, access to local heath care facilities, information needs and concerns, availability of carers, current health care, accommodation, education, leisure and social facilities.

A semi-structured interview was conducted on 45 patients to ensure that as broad a range of viewpoints over health care needs would be obtained. A pilot study was conducted in a selected non-randomised group of patients to develop and refine a novel questionnaire. Several wording and other amendments were made and some items were deleted after factor analysis to develop the final self-administered version.

Developing the questionnaire

There are two major sorts of health care needs among patients with suspected myocardial infarction; first general health care needs, which should be similar to those with similar demographic and socioeconomic characteristics; and second, specific needs that are perhaps unique to this patient group. Quality of life information obtained from the same patients was used as a 'gold standard'.

Questionnaire content

To take account of all available sources of information apposite to HNA in cardiac patients, a questionnaire battery which included more than 80 items was devised, based on a 'trial and error' approach. Patients were asked to provide feed back on any item which could not be easily understood or was not applicable. The first draft of the questionnaire, issued to patients admitted to hospital to ascertain its clarity and compatibility to their perceptions of health needs, contained several open-ended questions to allow the patients to record perceived health needs in their own words. Several amendments were then made in light of patients' comments or special needs.

During the development of the instrument, it was felt important to avoid jargon, negative, ambiguity, biased, 'double negative' and complex questions. The number of open-ended questions was intentionally limited. Questions containing 'options' were refined to get clearer answers. The average question length was 12 words. All related questions were placed in appropriate groups and the layout optimised for 'user-friendliness', readability and responsiveness. The assessment tool, which consists of 48 questions in 5-score Likert scale (1 indicates more needs versus 5 with no needs) in five domains of 'physical needs, 'satisfaction', 'informational needs', 'social needs, and 'concerns' (table 1). A mean score in each domain was computed to enable further calculations and comparisons with other variables.
Table 1

Nottingham Healthcare Needs Assessment questionnaire components

Domains

Items allocated

Mean score (SD)

Measure of skewness*

Cronbach's alpha

Corrected total-item correlation

Floor score (%)

Ceiling score (%)

Physical needs

8

3.64(0.93)

-2.58

0.88

0.59–0.85

1(0.4)

5 (2.1)

Satisfaction

11

4(0.76)

-4.53

0.87

0.55–0.75

1(0.4)

21 (8.7)

Informational needs

7

3.94(0.97)

-5.52

0.89

0.54–0.88

1(0.4)

14 (5.8)

Social needs

12

4.01(0.73)

-6.38

0.86

0.40–0.68

5(2.1)

3 (1.2)

Concerns

8

2.89(0.76)

0.37

0.83

0.50–0.79

1(0.4)

1 (0.4)

*Measures beyond ± 1.96 are significantly skewed at the level of 0.05.[28]

Demographic and a few specific questions such as the type of accommodation, intention or desire to move, attitude to health checks and the private health care sector were added. Following factor analysis, two of the 48 questions were removed. The first dealt with patients overall health perception during the preceding year (health transition). The second sought information about concerns regarding the threat of unemployment.

Seattle Angina Questionnaire (SAQ)

The SAQ has well-established psychometric properties, measures broader aspects of the effects of coronary disease than other disease-specific tools and can detect physical limitations due to coronary disease. It is particularly useful in the presence of co-morbidity [16] corresponding well with the Canadian Cardiovascular Society Classification [17]. The SAQ consists of 19 items grouped in five components: physical functioning (SAQ Phys), angina stability (AS), angina frequency (AF), treatment satisfaction (TS), and QOL perception (SAQ QOL).

Short Form 12 (SF-12)

The SF-12 is an abridged form of the better-known Short Form 36 (SF-36) [18] which has produced consistent results in several European countries and in a diverse range of conditions. It contains 12 questions from which are derived physical and mental component scores (PCS & MCS); these are as precise as the SF-36. [19, 20]

EuroQOL (EQ-5D)

The EuroQol questionnaire (EQ-5D) defines health in terms of five dimensions: mobility, self-care, usual activities, pain or discomfort, and anxiety or depression in a three degree format that is 'no problem', 'moderate' and 'severe'. Another question deals with overall health in a scaling (0–100) format. The validity and reliability of the EQ-5D questionnaire have been tested in a range of patient groups. [21, 22] There is a strong correlation between the EQ-5D and the SF-12 in adults,[23] but to our knowledge, there has been no published study of the EQ-5D in suspected or confirmed myocardial infarction.

Statistical analysis

SPSS version 11.0 was used for statistical purposes, using descriptive and correlation analysis, comparison of means, analysis of variance and multivariate (MANOVA), reliability and non-parametric (Mann-Whitney) tests where indicated. Several contingency tables were formed to look for significant correlation and chi-square test was used to measure the association between variables. As the majority of variables were in scaling format, Spearman rho was used to detect correlation, which was considered significant at p < 0.05. This survey was approved by the Local Ethical Committee.

Results

Demographic data

242 patients (59% male) returned the completed questionnaires. Ages ranged between 31–93 years (mean = 69.7, 95% CI: 68.2,71.2). Seventy-one percent (n = 169) left school at age 16 or less and 21% ( = 53) completed higher education. Table 2 describes the major demographic characteristics of all but 3 patients. Social class, derived from the last occupation, was determined in 223 patients. [24] 69 (31%) had non-manual and 154 (69%) manual jobs (table 2). Health status, in terms of QOL scores, is discussed below but generally women had lower mean scores in all QOL domains, which reached statistical significance in SAQ-AS and PCS (SF-12). (t = -2.04 and t = -1.99 respectively, P < 0.05) Patients over 65 years old had worse QOL scores in several domains of the three QOL tools. (P < 0.001)

Table 2

General information

Variable

 

N

Percent

Age group

=<54

29

12

 

55–64

47

20

 

65–74

73

30

 

75–84

67

28

 

>=85

23

10

Gender

Female

  
 

Male

143

 

Education level

School certificate

23

10

 

Left at age<16

146

66

 

"O" or "A" level

14

6

 

College or higher

39

18

Occupation

Retired

194

80.5

 

Unemployed

15

6

 

Full-time

24

10

 

Part-time

8

3

Diagnosis

Definite MI

27

11

 

Possible MI

34

14

 

IHD

152

64

 

Chest pain

26

11

Social class

I

3

1

 

II

35

16

 

III non-manual

31

14

 

III manual

62

28

 

IV

71

32

 

V

21

9

Type of accommodation

House

133

55

 

Flat

30

12

 

Bungalow

75

31

 

Nursing & park home

4

2

Live alone

Yes

76

31

 

No, with Spouse

153

63

 

No, with Children and others

13

6

Home satisfaction

dissatisfied

59

25

 

satisfied

181

75

Intention to move

No

177

78.0

 

Yes

50

22.0

Occupation

Patients were questioned about their current occupation and whether they had changed their job as a result of their illness; most were retired (Table 2). "Changes in patients' occupational status" did not correlate with diagnosis (P = 0.72), nor with gender, social class and education level, but apparently younger patients (<65 y) were more susceptible to change their job as a result of ill health. (P < 0.01) The unemployed were more likely to have changed jobs in the previous year (P < 0.01). Various components in EQ-5D, SAQ physical and PCS correlated significantly with both variables (p < 0.001). Patients who altered their job as a result of their health had a lower mean score in all QOL domains except SAQ treatment satisfaction. (MANOVA: F = 7.14–17.65, P < 0.01– < 0.001 in all domains except SAQ TS)

Home Circumstances

31% lived alone, women more so than men (41% female versus 24% male). These patients reported lower scores in all QOL domains, but this was significant only in SAQ physical domain (t = -2.1, P < 0.05). Satisfaction with current accommodation was not related diagnosis, comorbid illness or social class, but one-third of patients with psychological and respiratory disorders were unhappy with their accommodation (38% and 33% respectively).

Mean QOL scores were lower in patients who lived alone compared with others, significant in SAQ physical domain (mean 46.5 v 55.5, t = -2.17 P < 0.05). QOL was affected by intention to move, most significant in SAQ QOL and MCS (P < 0.001). Patients who were completely satisfied with accommodation perceived better health (mean MCS = 40.5) compared with those who were dissatisfied (mean MCS = 47.9, t-test = -4.5, P < 0.001). Patients who wished to move to a more suitable house had worse QOL (mean MCS = 40.5 v 48, P < 0.001).

Transport

Women were more likely to complain about transport. Dissatisfaction with means of transport affected patients' ease of access to healthcare facilities in both sexes (P < 0.001). Among patients who had difficulty in accessing healthcare facilities (N = 93; 38%) transport was their chief complaint. Those who relied upon public services and someone else's vehicle were more likely to be dissatisfied (P < 0.001).

Social support

Social activities were limited. 19% had no hobby, which was not related to age, sex, social class, diagnosis, or co-morbidity. 24% went out socially less than once per month; younger patients were less likely to have an active social life (P = 0.01). 29% felt that illness prevented their taking up or continuing a hobby. All were related to QOL. (Table 3)
Table 3

Correlation between social needs and HRQL components

 

EQ-Mob

EQ-SC

EQ-UA

EQ-PD

EQ-AD

EQ-VAS

SAQ Phys

SAQ AS

SAQ AF

SAQ TS

SAQ QOL

PCS

MCS

Social class

.18

.08

.09

.24

.05

-.22

-.13*

-.01

-.06

.01

-.15*

-.11

-.12

Feel satisfied with your accommodation?

-.19

-.05

-.12

-.06

-.25

.17

.15

.04

.18

.28

.24

.06

.28

Happy using this means of transport?

-.26

-.16

-.25

-.23

-.35

.28

.34

.13*

.24

.33

.34

.29

.33

How often go out socially?

-.17

-.17

-.20

-.12*

-.20

.17

.24

.15*

.15*

.02

.13*

.19

.25

Any difficulty getting Health Centre?

-.39

-.45

-.43

-.32

-.41

.44

.48

.24

.26

.15*

.32

.50

.38

Concerning give up job because of health

-.16

.30

-.22*

-.33

-.23*

.12

.13

.20

.16

.18

.21*

.16

.38

Your helper is happy to continue?

-.10

-.27

-.19*

-.13

-.39

.21*

.36

.21*

.29

.31

.37

.22*

.44

Looking after you causes problems for helper?

-.23

-.38

-.37

-.15

-.29

.29

.40

.24

.30

.28

.30

.30

.44

Need help to get out and about?

-.28

-.42

-.33

-.27

-.25

.31

.39

.08

.14*

.27

.28

.39

.26

Need financial help?

-.30

-.31

-.32

-.20

.34

.38

.38

.14*

.15*

.33

.31

.34

.46

Need seeing friends more?

-.29

-.32

-.31

-.32

-.40

.37

.44

.06

.17

.28

.31

.41

.42

Need visiting from Social worker?

-.29

-.33

-.29

-.26

-.28

.36

.43

.16*

.19

.28

.22

.33

.39

Need better housing?

-.29

-.21

-.30

-.22

-.33

.32

.29

.02

.25

.36

.33

.23

.41

Mean Social Needs score in HNA

-.44

-.41

-.48

-.36

-.54

.50

.55

.19

.32

.37

.45

.49

.63

* indicates P < 0.05 and boldface < 0.01

35% patients required financial support; younger more so than older patients (P < 0.001; OR = 1.4, CI: 1.12,1.77). Younger patients (<65 y) and manual workers were more concerned about financial assistance (t = 2.99 and -2.72 respectively, P < 0.01). One third of patients sought help with household cleaning chores and for social contacts and one-fifth wanted regular visits by a social or other worker. Patients with co-morbidity were more likely to require help with cleaning (P < 0.05; OR = 2.5 CI: 1.1,5.4).

30% assumed that seeing friends might help them to better deal with and overcome their illness; retired and unemployed were 10 times more likely to have unmet social needs. (P < 0.001; OR = 10.4, CI: 1.5,74). Comorbidity increased the likelihood of wanting social help (P = 0.01; OR = 3 CI: 1.1,7.9). Women and IHD patients were more likely to be concerned about help with cleaning (t = 2.85 and -2.35, P < 0.01 and <0.05 respectively).

Help needs

119 patients expressed a need for care, which was related to diagnosis (P < 0.01). 18% of patients who needed a carer ( = 21) had no support. Women were particularly vulnerable (P < 0.001); 10 out of 51 patients who needed a carer had nobody to support them. Patients were questioned whether their helpers were happy to continue caring; 42% (n = 47) were concerned their helpers might have to discontinue helping. Patients who already benefited from a helper at home and patients who requested a helper had significant lower HRQL and HNA scores. Patients with no company at home had more physical and social needs (p < 0.01) and impaired HRQL (p < 0.05). (Table 5)

Table 4

Correlation between physical needs and HRQL components

 

EQ-Mob

EQ-SC

EQ-UA

EQ-PD

EQ-AD

EQ-VAS

SAQ Phys

SAQ AS

SAQ AF

SAQ TS

SAQ QOL

PCS

MCS

Illness stops your hobbies?

-.40

-.25

-.48

-.44

-.34

.52

.53

.19

.35

.28

.47

.59

.41

Your health prevents you going out?

-.53

-.48

-.51

-.49

-.41

.59

.66

.20

.36

.24

.45

.67

.34

Have problems getting around

-.56

-.49

-.56

-.57

-.37

.62

.66

.28

.28

.16*

.43

.67

.38

Need anyone look after you?

-.45

-.63

-.51

-.43

-.35

.59

.62

.19

.23

.12

.31

.60

.34

Need any equipment for daily activities?

-.41

-.45

-.38

-.38

-.24

.41

.51

.19

.19

.21

.25

.41

.29

Moving concern?

-.62

-.61

-.64

-.56

-.45

.62

.71

.26

.35

.19

.48

.71

.46

Need cleaning help?

-.32

-.34

-.37

-.26

-.30

.39

.48

.13

.21

.33

.21

.45

.36

Need getting out help?

-.39

-.41

-.46

-.34

-.50

.49

.55

.13

.25

.26

.34

.52

.46

Mean Physical Needs score in HNA

-.59

-.60

-.62

-.56

-.48

.69

.76

.26

.35

.29

.45

.75

.48

* indicates P < 0.05 and boldface < 0.01

Overall social needs

To gain an overall estimation of health needs in social domain a score for each patient was calculated. Patients over 65 years (p < 0.05) and with higher social classes (p < 0.01) had more social needs but there was no significant difference among gender, education nor their diagnosis. Patients with higher physical needs had apparently more social needs, too (p < 0.001). Social needs score was low to moderately (0.32 < r < 0.63) correlated with all (except SAQ-AS) domains in HRQL tools. (Table 3)

Overall physical needs

Similarly an individual score was computed for each patient to demonstrate the overall physical aids and its association with HRQL scores. Table 4 shows that the SAQ physical component, Physical Component Score in SF-12, and the visual analogue scale in the EQ-5D are all highly (correlation coefficient more than 0.70) correlated with the HNA physical score (p < 0.001). More physical needs were detected in elderly (p < 0.01) and ischaemic patients (p < 0.05) compared with confirmed MI. No gender difference was observed in physical needs.
Table 5

Comparing HRQL and HNA domains means in various help needs

  

EQ-Mob

EQ-SC

EQ-UA

EQ-PD

EQ-AD

EQ-VAS

SAQ Phys

SAQ AS

SAQ AF

SAQ TS

SAQ QOL

PCS

MCS

HNA phys

HNA Sat

HNA Info

HNA Soc

HNA Con

company

MW-U

5483

5751

5237

5779

5707

5688

4659

5310

5677

5147

5828

4617

4442

4441

5870

5795

4783

6242

 

Z

-1.60

-1.09

-1.80

-.83

-.90

-.62

-2.30*

-.77

-.16

-.79

-.25

-1.02

-1.43

-3.56

-.86

-1.02

-3.01

-.13

Help needs

MW-U

4103

4163

3303

3779

4619

2500

2315

5629

4897

5348

4434

2052

3895

941

5899

4866

3215

3579

 

Z

-6.65

-7.51

-7.70

-6.80

-5.00

-8.40

-8.51

-2.37*

-3.53

-1.99*

-4.50

-8.34

-4.39

-11.56

-2.22*

-4.20

-7.28

-6.59

Looking after patients

MW-U

4750

5060

4782

5320

5485

4184

3357

6207

5787

6295

5695

3153

4693

2742

7243

6461

4974

4860

 

Z

-5.39

-5.30

-4.78

-3.71

-3.36

-5.30

-6.65

-1.16

-2.01*

-.29

-2.32*

-5.97

-2.66

-8.29

-.03

-1.48

-4.22

-4.43

Boldface indicates p < 0.001 and *<0.05

Discussion

The medical model of health care has led to major improvement in health in the Western world but resolving the clinical aspects of an illness ignores the impact on quality of life in the patient's social context, generating unmet need. We identified several areas which warrant further investigation and implications for clinical practice.

Accommodation was a major concern for many, adversely affecting health-related quality of life in one in five patients, independent of age and diagnosis or existing house size. Social problems were common but two in particular are worthy of attention. First, living alone created difficulties. This is a timely reminder that the family environment should be considered when medical treatment is offered. [25] Second was social isolation, a major psychological factor that has been acknowledged as important aid to survival following an acute myocardial infarction, particularly in vulnerable groups like elder patients or women. [9, 26] One-third of our patients assumed that a wider social circle might help them to cope with and better overcome their illness. Being in employment facilitates social contact, and our non-working groups, whether retired or not were 10 times more likely to request improved social communication. In this respect, attendance at post-myocardial infarction rehabilitation groups assumed greater importance, especially for lower socio-economic groups who are notoriously poor at accepting invitations for cardiac rehabilitation; [27] in addition, the role of the traditional outpatient appointment becomes more important for some as a social rather than medical event. Overall individual patients' social needs and physical needs scores correlated "moderate to high" [28] with all HRQL components, which supports the construct validity of the needs assessment questionnaire.

The impact of socio-economic status on health, as well as on equity of access [29] have been known for many years. [30] In line with other reports [29], knowing how to get the best out of the medical services and gaining access to healthcare facilities, particularly gaining information about illness or discussing concerns about diagnosis or prognosis, is directly related to socio-economic status. The impact of socio-economic status, although not universal,.[31] highlights the difficulty of ensuring equity of access to standard care for everyone in the community. One way to tackle this is to identify vulnerable patients and communities and target these.

We confirmed age and gender differences in health related quality of life reported by others. [32] Quality of life was perceived to be worse in older patients. In addition to gender variations in etiological factors and the well-known excess of coronary heart disease in men, differences in access to diagnostic and treatment procedures have been reported. [33] Our results – similar to other studies[34] – indicate that women had worse quality of life in all domains, which per se contribute to lower survival chances. Women also required more help needs and social support consistent with evidence from other studies. [25, 35]

The needs expressed by our patient population identifies areas for potential improvements in health care that are usually not directly related to physical conditions and therefore are generally ignored by healthcare professionals. If assessing needs leads to genuine change in the current healthcare services [36] where health is the ultimate concept of well-being, meeting social, physical, transport and housing needs ought to provide a more comprehensive health care, and improve the outcome, for patients.

Establishing need presents problems and the Nottingham Health Needs Assessment was developed for this study because health needs analysis is a relatively new approach to ascertaining attitudes to health and so there was no 'off the shelf' valid and reliable needs assessment instrument available for cardiac patients. The tool, however, showed acceptable psychometric properties (table 1) and therefore we propose to test this instrument more widely to assess its generalisability against a background of a wide range of patient demography, illnesses and socio-economic and geographic settings.

Based on an analysis of a pilot study and experience gained in routine clinical visits, we had expected that our patients might have common social health needs as well as specific health needs relating to their illness. What surprised us was the depth of the underlying current of major deficiencies in social or health service provision which generated considerable dissatisfaction with quality of life, despite satisfactory resolution of presenting symptoms. Resolving social and environmental issues remains an important issue in the era of ever-increasing medical technology, not least in coronary heart disease.

Authors’ Affiliations

(1)
Division of Cardiovascular Medicine, University Hospital
(2)
Division of Epidemiology & Public Health, University of Nottingham

References

  1. Bradshaw J: A taxonomy of social need. Problems and progress in medical care: essays on current research, 7th series (Edited by: Mclachlan G). Oxford, Nuffield Provincial Hospital Trust 1972.Google Scholar
  2. Stevens A, Gabbay J: Needs assessment needs assessment. Health Trends 1991, 23: 20–23.PubMedGoogle Scholar
  3. James M: Towards an integrated needs and outcome framework. Health Policy 1999, 46: 165–177. 10.1016/S0168-8510(98)00064-5PubMedView ArticleGoogle Scholar
  4. Robinson J, Elkan R: Health needs assessment, theory and practice. New York, Churchill Livingstone 1996.Google Scholar
  5. Wilkinson JR, Murray SA: Health needs assessment - Assessment in primary care: practical issues and possible approaches. BMJ 1998, 316: 1524–1528.PubMed CentralPubMedView ArticleGoogle Scholar
  6. Ruta DA, Duffy MC, Farquharson A, Young AM, Gilmour FB, McElduff SP: Determining priorities for change in primary care: the value of practice-based needs assessment. Br J Gen Pract 1997, 47: 353–357.PubMed CentralPubMedGoogle Scholar
  7. Stevens A, Gillam S: Needs assessment: from theory to practice. BMJ 1998, 316: 1448–1452.PubMed CentralPubMedView ArticleGoogle Scholar
  8. Herlitz J, Hjalmarson A, Karlson BW, Nyberg G: Long-term morbidity in patients where the initial suspicion of myocardial infarction was not confirmed. Clin Cardiol 1988, 11: 209–214.PubMedView ArticleGoogle Scholar
  9. Murray SA, Boyd K, Kendall M, Worth A, Benton TF, Clausen H: Dying of lung cancer or cardiac failure: prospective qualitative interview study of patients and their carers in the community. BMJ 2002, 325: 929. 10.1136/bmj.325.7370.929PubMed CentralPubMedView ArticleGoogle Scholar
  10. Patrick DL, Deyo RA: Generic and disease-specific measures in assessing health status and quality of life. Med Care 1989, 27: S217–32.PubMedView ArticleGoogle Scholar
  11. Engstrom CP, Persson LO, Larsson S, Sullivan M: Health-related quality of life in COPD: why both disease-specific and generic measures should be used. Eur Respir J 2001, 18: 69–76. 10.1183/09031936.01.00044901PubMedView ArticleGoogle Scholar
  12. Guyatt GH, Bombardier C, Tugwell PX: Measuring disease-specific quality of life in clinical trials. CMAJ 1986, 134: 889–895.PubMed CentralPubMedGoogle Scholar
  13. Guyatt GH, Veldhuyzen Van Zanten SJ, Feeny DH, Patrick DL: Measuring quality of life in clinical trials: a taxonomy and review. CMAJ 1989, 140: 1441–1448.PubMed CentralPubMedGoogle Scholar
  14. Wiklund I, Karlberg J: Evaluation of quality of life in clinical trials. Selecting quality-of-life measures. Control Clin Trials 1991, 12: 204S-216S..PubMedView ArticleGoogle Scholar
  15. Gray D, Hampton JR: Twenty years' experience of myocardial infarction: the value of a heart attack register. Br J Clin Pract 1993, 47: 292–295.PubMedGoogle Scholar
  16. Spertus JA, Winder JA, Dewhurst TA, Deyo RA, Fihn SD: Monitoring the quality of life in patients with coronary artery disease. Am J Cardiol 1994, 74: 1240–1244.PubMedView ArticleGoogle Scholar
  17. Dougherty CM, Dewhurst T, Nichol WP, Spertus J: Comparison of three quality of life instruments in stable angina pectoris: Seattle Angina Questionnaire, Short Form Health Survey (SF-36), and Quality of Life Index-Cardiac Version III. J Clin Epidemiol 1998, 51: 569–575. 10.1016/S0895-4356(98)00028-6PubMedView ArticleGoogle Scholar
  18. Brazier JE, Harper R, Jones NM, O'Cathain A, Thomas KJ, Usherwood T, Westlake L: Validating the SF-36 health survey questionnaire: new outcome measure for primary care. BMJ 1992, 305: 160–164.PubMed CentralPubMedView ArticleGoogle Scholar
  19. Gandek B, Ware JE, Aaronson NK, Apolone G, Bjorner JB, Brazier JE, Bullinger M, Kaasa S, Leplege A, Prieto L, Sullivan M: Cross-validation of item selection and scoring for the SF-12 Health Survey in nine countries: results from the IQOLA Project. International Quality of Life Assessment. J Clin Epidemiol 1998, 51: 1171–1178. 10.1016/S0895-4356(98)00109-7PubMedView ArticleGoogle Scholar
  20. Jenkinson C, Layte R, Jenkinson D, Lawrence K, Petersen S, Paice C, Stradling J: A shorter form health survey: can the SF-12 replicate results from the SF-36 in longitudinal studies? J Public Health Med 1997, 19: 179–186.PubMedView ArticleGoogle Scholar
  21. Kind P, Dolan P, Gudex C, Williams A: Variations in population health status: results from a United Kingdom national questionnaire survey. BMJ 1998, 316: 736–741.PubMed CentralPubMedView ArticleGoogle Scholar
  22. van Agt HM, Essink-Bot ML, Krabbe PF, Bonsel GJ: Test-retest reliability of health state valuations collected with the EuroQol questionnaire. Soc Sci Med 1994, 39: 1537–1544. 10.1016/0277-9536(94)90005-1PubMedView ArticleGoogle Scholar
  23. Johnson JA, Coons SJ: Comparison of the EQ-5D and SF-12 in an adult US sample. Qual Life Res 1998, 7: 155–166. 10.1023/A:1008809610703PubMedView ArticleGoogle Scholar
  24. Standard occupational classification /Office for National Statistics. London, Stationery Office 2000.Google Scholar
  25. Janz NK, Janevic MR, Dodge JA, Fingerlin TE, Schork MA, Mosca LJ, Clark NM: Factors influencing quality of life in older women with heart disease. Med Care 2001, 39: 588–598. 10.1097/00005650-200106000-00007PubMedView ArticleGoogle Scholar
  26. Mendes de Leon CF, Dilillo V, Czajkowski S, Norten J, Schaefer J, Catellier D, Blumenthal JA: Psychosocial characteristics after acute myocardial infarction: the ENRICHD pilot study. Enhancing Recovery in Coronary Heart Disease. J Cardiopulm Rehabil 2001, 21: 353–362. 10.1097/00008483-200111000-00003PubMedView ArticleGoogle Scholar
  27. Melville MR, Packham C, Brown N, Weston C, Gray D: Cardiac rehabilitation: socially deprived patients are less likely to attend but patients ineligible for thrombolysis are less likely to be invited. Heart 1999, 82: 373–377.PubMed CentralPubMedView ArticleGoogle Scholar
  28. Munro HB: Statistical methods for health care research. 4 Edition Philadelphia, Lippincott Williams & Wilkins 2001.Google Scholar
  29. Richards H, McConnachie A, Morrison C, Murray K, Watt G: Social and gender variation in the prevalence, presentation and general practitioner provisional diagnosis of chest pain. J Epidemiol Community Health 2000, 54: 714–718. 10.1136/jech.54.9.714PubMed CentralPubMedView ArticleGoogle Scholar
  30. Townsend P, Whitehead M, Davidson M: Inequalities in health. 2nd Edition London, Penguin 1992.Google Scholar
  31. Finkelstein MM: Do factors other than need determine utilization of physicians' services in Ontario? CMAJ 2001, 165: 565–570.PubMed CentralPubMedGoogle Scholar
  32. Ades PA, Savage PD, Tischler MD, Poehlman ET, Dee J, Niggel J: Determinants of disability in older coronary patients. Am Heart J 2002, 143: 151–156. 10.1067/mhj.2002.119379PubMedView ArticleGoogle Scholar
  33. Majeed FA, Cook DG: Age and sex differences in the management of ischaemic heart disease. Public Health 1996, 110: 7–12.PubMedView ArticleGoogle Scholar
  34. Varvaro FF, Olds NB, Zullo TG, Murali S: Determining Quality of Life in Older and Younger Women With Congestive Heart Failure and Myocardial Infarction. Am J Geriatr Cardiol 1999, 8: 15–20.PubMedGoogle Scholar
  35. Loose MS, Fernhall B: Differences in quality of life among male and female cardiac rehabilitation participants. J Cardiopulm Rehabil 1995, 15: 225–231.PubMedView ArticleGoogle Scholar
  36. Hawe P: Needs assessment must become more change-focused. Aust N Z J Public Health 1996, 20: 473–478.PubMedView ArticleGoogle Scholar

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