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Chronic disease management items in general practice: a population-based study of variation in claims by claimant characteristics

Kirsty A Douglas, Laurann E Yen, Rosemary J Korda, Marjan Kljakovic and Nicholas J Glasgow
Med J Aust 2011; 195 (4): 198-202. || doi: 10.5694/j.1326-5377.2011.tb03279.x
Published online: 15 August 2011

Abstract

Objective: To describe how Medical Benefits Schedule (MBS) chronic disease (CD) item claims vary by sociodemographic and health characteristics in people with heart disease, asthma or diabetes.

Design, setting and participants: A cross-sectional analysis of linked unit-level MBS and survey data from the first 102 934 participants enrolled in the 45 and Up Study, a large-scale cohort study in New South Wales, who completed the baseline survey between January 2006 and July 2008.

Main outcome measure: Claim for any general practitioner CD item within 18 months before enrolment, ascertained from MBS records.

Results: The proportion of individuals making claims for MBS CD items was 18.5% for asthma, 22.3% for heart disease, and 44.9% for diabetes. Associations between participant characteristics and a claim for a CD item showed similar patterns across the three diseases. For heart disease and asthma, people most likely to claim a CD item were women, older, of low income and education levels, with multiple chronic conditions, fair or poor self-rated health, obesity and low physical activity levels. The pattern of claims was slightly different for participants with diabetes in that there was no significant association with number of chronic conditions, smoking or physical activity.

Conclusions: Many individuals with self-reported CD do not claim CD items. People with diabetes and individuals with greatest need based on health, socioeconomic and lifestyle risk factors are the most likely to claim CD items.

Methods

We used data from the 45 and Up Study, a large-scale cohort study involving men and women aged 45 years and over from New South Wales, Australia.16

Participants in the study were randomly sampled from the Medicare database, which provides virtually complete coverage of the Australian population. They joined the study by completing a baseline questionnaire.17 All participants gave signed consent for follow-up and linkage to a range of health databases. We used data on the first 102 934 participants enrolled in the study, who completed the baseline questionnaire between January 2006 and July 2008. We selected participants with heart disease, diabetes or asthma, based on their response to the question “Has a doctor ever told you that you have ...” followed by a list of 14 common chronic or complex conditions, including heart disease, diabetes, and asthma (listed separately from January 2007). Survey data for each participant were linked to MBS data, which included records of every medical service claimed by study participants since July 2004. These records contain MBS item numbers and the date on which each service was received. All participants were enrolled at least 18 months after June 2004, enabling an adequate time period to capture claims for a CD management service.

The outcome variable was the claim for any general practitioner CD item number (MBS Items 721–732) within 18 months before enrolment in the study, which was coded as a dichotomous variable (1 = yes; 0 = no). For patients with asthma, the outcome variable was also coded as 1 if the participant had claimed an asthma annual cycle of care service (MBS Items 2546–2559 and 2664–2677). For patients with diabetes, the outcome variable was also coded as 1 if the participant had claimed a diabetes annual cycle of care service (MBS Items 2517–2526 and 2620–2635). Sociodemographic and health-related exposure variables were based on self-reported data collected on the baseline survey. The main sociodemographic variables of interest were sex, age, area of residence, education and household income, and the health variables of interest were overall self-rated health, body mass index, smoking, physical activity, alcohol consumption and other chronic conditions from the list of those available (Box). Other variables (data not shown) included country of birth (Australia, New Zealand, elsewhere), marital status (married, de facto, not married), area-based socioeconomic status (SES) (quintiles of disadvantage based on Socio-Economic Indexes for Areas,18 derived from postcode of residence), employment status (employed/retired/not employed) and Health Care Card (yes/no).

The strength of association between each sociodemographic or health variable and a CD item claim for people reporting heart disease, asthma and diabetes was estimated using logistic regression, with the results presented as odds ratios adjusted for age and sex. Analyses were conducted using Stata, version 11.1 (StataCorp, College Station, Tex, USA). Two sensitivity analyses were done to examine potential biases. The first analysis involved excluding participants who were diagnosed within the 18 months before enrolment, to limit the analysis to those who were potentially eligible for a CD item for the full 18 months. The second analysis excluded participants who enrolled before January 2007, to limit the analysis to the period after introduction of the new CD items (in July 2005).

Results

After excluding those for whom Medicare data were not yet linked at the time of this study (1044, 1%), there were 12 545 people identified with heart disease, 7659 with asthma and 9113 with diabetes.

Among participants with heart disease, just over a fifth (22.3%) claimed at least one CD item in the 18 months before their enrolment in the study. Associations between patient characteristics and a claim for a CD item were significant for all the factors except smoking (Box). People most likely to claim a CD item were women; older (aged above 54 years); of lower SES (ie, for income and education); living in an inner regional area (least likely in remote areas); in relatively poor health (ie, multiple chronic conditions, fair or poor self-rated health, obese, low physical activity levels); and non-drinkers. Claimants were also less likely to have private health insurance or a DVA (Department of Veterans’ Affairs) treatment card.

Among people with asthma, less than one in five (18.5%) claimed a CD item in the 18 months before their enrolment in the study, and only 1.5% claimed an asthma annual cycle of care service. Associations between patient characteristics and claims for a CD item showed a very similar pattern to that of people with heart disease (Box). However, among people with asthma (unlike among those with heart disease), past smokers and current smokers were more likely to have claimed a CD item than participants who had never smoked.

Among participants with diabetes, almost half (44.9%) claimed a CD item, with 23.1% claiming a diabetes annual cycle of care service. The pattern of service use with respect to sociodemographic and health characteristics was slightly different compared with the patterns found among people with heart disease and asthma. Participants with diabetes who lived in remote areas were more likely to claim a CD item than those living in major cities, and there was no association with number of chronic conditions, smoking or physical activity. People most likely to claim a CD item were women; aged 65–74 years; of lower SES (income and education); obese; without a DVA card or private insurance; and non-drinkers (Box).

In addition to the results shown in the Box, people with heart disease, asthma or diabetes were significantly less likely to claim a CD item if they lived in areas of least disadvantage, were currently employed, and did not have a Health Care Card. These findings, like those above, show a greater probability of a CD claim among people of low SES. Among people with heart disease, those born outside Australia or New Zealand were significantly more likely to claim a CD item than those born in Australia or New Zealand, while the reverse was true among those with diabetes. Among people with heart disease or asthma, those who were not married were significantly more likely to claim an item than those who were married or in a de facto relationship (data available on request).

We also separately examined a subset of the CD items — for Team Care Arrangements (TCAs) (Items 723 and 727) — and found that about half of those with any CD item had claimed a TCA item (data available on request). The pattern and strength of association between these TCA items and sociodemographic and health characteristics were very similar to those reported above for any CD item. The two sensitivity analyses showed results to be essentially unchanged after excluding participants who were diagnosed within the 18 months before enrolment, and after excluding only those who enrolled before January 2007.

Discussion

Our study is the first to link unit-level survey and MBS data to examine claims for MBS CD items. We have shown that while the majority of people with heart disease, asthma or diabetes do not claim CD items, such items are most likely to be claimed by individuals of low income, low educational attainment, and poor health. Individuals with different lifestyle risk factors also have different claim patterns. High body mass index, and in some cases levels of physical activity and smoking, are also associated with an increased likelihood of a claim.

Strengths of our study include the large number of participants and the ability to link individual survey data to MBS records. The study examines CD item claims made between 7 and 9 years after the EPC package was launched, at least 2 years after changes were made in item descriptors, and following significant government and Division of General Practice promotion. Thus the study reflects the use of the items in a mature policy environment. A limitation is that no case note review of care was undertaken and some individuals may have had formal CD management plans created but never claimed against the item number. Another limitation is that all exposure data were self-reported. In particular, self-report of morbidity has well known methodological limitations, and the simple enumeration of chronic conditions from a restricted list, with no assessment of severity or time since diagnosis, is a crude measure of comorbidity.

There are no previous studies with which we can directly compare our results. Our finding that women and those with multiple chronic conditions are the most likely to claim CD items is similar to that of a recent clinically based study on TCAs;15 and our finding that people of lower SES are more likely to claim CD items than those with higher SES is consistent with a study based on MBS data aggregated by SES of postcode of general practice.12,19 This suggests that these items are claimed by those most in need. In contrast to aggregate-level studies,19 but similar to the individual level study of TCAs,15 we found that people (with asthma and heart disease at least) had a significantly decreased likelihood of claiming for a CD item in remote areas compared with major cities. As access to Medicare rebates for allied health services is a driver of some of the CD items,13 the relative paucity of available allied health services in remote areas may go some way to explaining this finding.

There were significant differences in the patterns of MBS CD item use across the three CDs. This suggests that GPs discriminate, perhaps appropriately, between conditions when they consider making a CD management plan. For patients with diabetes, the proportion of patients who claimed at least one CD item was nearly double that for people with either heart disease or asthma. The reasons for this greater use may include the emphasis given to diabetes management in Division of General Practice education and practice support programs, and the influence of accepted best practice guidelines for management and monitoring in diabetes.20 It may also reflect the fact that the original EPC items were designed around multidisciplinary practice, and diabetes management best practice explicitly involves other specified professionals.20,21 The relatively low proportion of participants with asthma who claimed an item may reflect the fact that asthma is not necessarily a current problem for many participants.

Many individuals with chronic conditions do not claim CD management items, but those who appear to have greatest need, based on health, socioeconomic and lifestyle risk factors, are the most likely to claim them. Further, CD items are claimed most for individuals with diabetes, where the evidence to support structured and multidisciplinary care is strongest. This suggests that Australian GPs are more likely to adopt policy when it is supported by good evidence. Further studies assessing whether MBS CD items are associated with improvements in health outcomes are needed.

Number of people with heart disease, asthma or diabetes who claimed a chronic disease item in the 18 months before enrolment in the study (Jan 2006), by sociodemographic and health characteristics, and associated odds ratios adjusted for age and sex

Heart disease


Asthma


Diabetes


Total

No. of claims

Odds ratio (95% CI)

P

Total

No. of claims

Odds ratio (95% CI)

P

Total

No. of claims

Odds ratio (95% CI)

P


Total

12 545

2800 (22.3%)

7659

1418 (18.5%)

9113

4088 (44.9%)

Sex

Male

8243

1787 (21.7%)

1.00

3072

543 (17.7%)

1.00

5328

2281 (42.8%)

1.00

Female

4302

1013 (23.6%)

1.16 (1.06–1.26)

0.001

4587

875 (19.1%)

1.27 (1.12–1.43)

< 0.001

3785

1807 (47.7%)

1.27 (1.16–1.38)

< 0.001

Age (years)

45–54

1022

131 (12.8%)

1.00

2232

235 (10.5%)

1.00

1271

445 (35.0%)

1.00

55–64

2842

546 (19.2%)

1.61 (1.33–1.95)

< 0.001

2500

384 (15.4%)

2.16 (1.65–2.81)

< 0.001

2630

1127 (42.9%)

1.98 (1.57–2.49)

< 0.001

65–74

3821

954 (25.0%)

2.33 (1.94–2.79)

< 0.001

1668

441 (26.4%)

4.07 (3.09–5.37)

< 0.001

2850

1414 (49.6%)

2.77 (2.20–3.48)

< 0.001

75–84

3905

967 (24.8%)

2.31 (1.93–2.78)

< 0.001

1067

313 (29.3%)

4.69 (3.51–6.26)

< 0.001

1969

950 (48.3%)

2.13 (1.67–2.70)

< 0.001

≥ 85

955

202 (21.2%)

1.92 (1.53–2.39)

< 0.001

192

45 (23.4%)

3.35 (0.34–32.7)

0.298

393

152 (38.7%)

2.51 (0.15–40.6)

0.517

Area of residence*

Major cities

5980

1313 (22.0%)

1.00

3305

638 (19.3%)

1.00

4229

1746 (41.3%)

1.00

Inner regional

4230

1076 (25.4%)

1.23 (1.12–1.35)

< 0.001

2726

526 (19.3%)

1.02 (0.89–1.17)

0.758

3107

1546 (49.8%)

1.38 (1.25–1.52)

< 0.001

More remote

2323

410 (17.7%)

0.78 (0.69–0.86)

< 0.001

1623

254 (15.7%)

0.79 (0.67–0.93)

0.006

1772

793 (44.8%)

1.13 (1.01–1.27)

0.033

Education

No school qualification

1957

525 (26.8%)

1.00

985

250 (25.4%)

1.00

1675

841 (50.2%)

1.00

School Certificate/trade/apprenticeship

5792

1364 (23.6%)

0.86 (0.77–0.97)

0.015

3002

613 (20.4%)

0.82 (0.69–0.98)

0.026

4247

1953 (46.0%)

0.88 (0.78–0.98)

0.024

Certificate/diploma/degree

4472

820 (18.3%)

0.66 (0.58–0.75)

< 0.001

3510

503 (14.3%)

0.64 (0.54–0.77)

< 0.001

2925

1163 (39.8%)

0.71 (0.63–0.81)

< 0.001

Income

< $20 000

3826

1082 (28.3%)

1.00

1652

487 (29.5%)

2925

1436 (49.1%)

$20 000– < $40 000

2735

599 (21.9%)

0.72 (0.64–0.81)

< 0.001

1320

280 (21.2%)

0.71 (0.60–0.85)

< 0.001

1839

860 (46.8%)

0.94 (0.83–1.05)

0.265

$40 000– < $70 000

1662

272 (16.4%)

0.54 (0.47–0.63)

< 0.001

1306

157 (12.0%)

0.42 (0.34–0.51)

< 0.001

1165

451 (38.7%)

0.73 (0.63–0.84)

< 0.001

≥ $70 000

1458

161 (11.0%)

0.37 (0.31–0.45)

< 0.001

1833

157 (8.6%)

0.34 (0.27–0.42)

< 0.001

1007

325 (32.3%)

0.59 (0.50–0.69)

< 0.001

Missing data

2864

686 (24.0%)

0.81 (0.73–0.91)

< 0.001

1548

337 (21.8%)

0.71 (0.60–0.83)

< 0.001

2177

1016 (46.7%)

0.91 (0.81–1.01)

0.087

Private insurance/DVA card

None

4875

1325 (27.2%)

1.00

2794

676 (24.2%)

1.00

4166

2056 (49.4%)

1.00

Hospital insurance

6801

1405 (20.7%)

0.71 (0.65–0.77)

< 0.001

4711

727 (15.4%)

0.62 (0.55–0.70)

< 0.001

4542

1966 (43.3%)

0.8 (0.74–0.88)

< 0.001

DVA card

693

39 (5.6%)

0.14 (0.10–0.19)

< 0.001

116

9 (7.8%)

0.17 (0.09–0.34)

< 0.001

344

46 (13.4%)

0.15 (0.11–0.20)

< 0.001

Hospital insurance and DVA card

176

31 (17.6%)

0.51 (0.34–0.75)

0.001

38

6 (15.8%)

0.4 (0.16–0.97)

0.043

61

20 (32.8%)

0.47 (0.27–0.81)

0.007

Self-rated health

Excellent/very good

3580

628 (17.5%)

1.00

3106

335 (10.8%)

1.00

2309

970 (42.0%)

1.00

Good

4970

1092 (22.0%)

1.29 (1.16–1.44)

< 0.001

2729

542 (19.9%)

1.86 (1.60–2.16)

< 0.001

3631

1655 (45.6%)

1.16 (1.04–1.29)

0.007

Fair/poor

3647

979 (26.8%)

1.69 (1.51–1.89)

< 0.001

1644

485 (29.5%)

3.1 (2.64–3.63)

< 0.001

2893

1337 (46.2%)

1.2 (1.07–1.34)

0.002

Other chronic conditions

None

2860

466 (16.3%)

1.00

1863

205 (11.0%)

1.00

1802

758 (42.1%)

1.00

One

4587

939 (20.5%)

1.27 (1.12–1.44)

< 0.001

2897

446 (15.4%)

1.35 (1.13–1.62)

0.001

3480

1569 (45.1%)

1.07 (0.95–1.20)

0.256

Two

3142

794 (25.3%)

1.63 (1.44–1.86)

< 0.001

1780

422 (23.7%)

2.05 (1.70–2.47)

< 0.001

2301

1076 (46.8%)

1.1 (0.97–1.25)

0.139

Three or more

1956

601 (30.7%)

2.12 (1.85–2.44)

< 0.001

1119

345 (30.8%)

2.59 (2.12–3.17)

< 0.001

1530

685 (44.8%)

0.99 (0.86–1.14)

0.907

Body mass index (kg/m2)

Underweight (< 18.5)

162

32 (19.8%)

0.95 (0.64–1.42)

0.809

94

25 (26.6%)

1.81 (1.11–2.94)

0.017

60

26 (43.3%)

1.03 (0.61–1.74)

0.92

Healthy weight (18.5– < 25)

3920

795 (20.3%)

1.00

2327

377 (16.2%)

1.00

1759

730 (41.5%)

1.00

Overweight (25–30)

4812

1045 (21.7%)

1.14 (1.02–126)

0.019

2597

434 (16.7%)

1.1 (0.95–1.29)

0.211

3115

1371 (44.0%)

1.11 (0.98–1.25)

0.088

Obese (> 30)

2674

691 (25.8%)

1.52 (1.35–1.72)

< 0.001

1976

445 (22.5%)

1.66 (1.42–1.94)

< 0.001

3348

1570 (46.9%)

1.31 (1.16–1.58)

< 0.001

Smoking

Current smoker

667

137 (20.5%)

1.00

538

102 (19.0%)

1.00

658

258 (39.2%)

1.00

Past smoker

6129

1399 (22.8%)

0.96 (0.79–1.18)

0.705

3001

631 (21.0%)

0.82 (0.65–1.05)

0.119

4147

1861 (44.9%)

1.14 (0.96–1.35)

0.134

Never smoker

5698

1246 (21.9%)

0.89 (0.72–1.09)

0.25

4092

673 (16.5%)

0.64 (0.50–0.81)

< 0.001

4267

1943 (45.5%)

1.13 (0.95–1.34)

0.167

Physical activity§

Low

4110

976 (23.8%)

1.00

2331

477 (20.5%)

1.00

3456

1527 (44.2%)

1.00

Moderate

4259

919 (21.6%)

0.88 (0.80–0.98)

0.018

2583

468 (18.1%)

0.87 (0.75–1.00)

0.053

2891

1341 (46.4%)

1.08 (0.97–1.19)

0.156

High

3871

831 (21.5%)

0.89 (0.80–0.99)

0.039

2545

423 (16.6%)

0.82 (0.70–0.95)

0.007

2500

1095 (43.8%)

0.99 (0.89–1.10)

0.855

Alcohol (drinks per week)

None

4488

1148 (25.6%)

1.00

2706

631 (23.3%)

1.00

4185

2018 (48.2%)

1.00

< 15

5936

1229 (20.7%)

0.76 (0.71–0.85)

< 0.001

3759

575 (15.3%)

0.65 (0.57–0.74)

< 0.001

3622

1549 (42.8%)

0.84 (0.76–0.92)

< 0.001

≥ 15

1837

357 (19.4%)

0.74 (0.64–0.85)

< 0.001

1055

180 (17.1%)

0.78 (0.64–0.95)

0.014

1024

403 (39.4%)

0.74 (0.64–0.86)

< 0.001


* Area of residence based on ARIA+ (Accessibility/Remoteness Index of Australia Plus), derived from postcode of residence. DVA card is Department of Veterans’ Affairs treatment card, which is issued to veterans, their war widows and widowers and dependants, which enhances access to various health care services. Full list of other conditions and survey questions available at: http://www.45andup.org.au/studymaterialsandpublications.aspx § Physical activity is based on number of weekly sessions of at least 10 minutes duration, weighted for intensity, divided into tertiles.

  • Kirsty A Douglas1
  • Laurann E Yen2
  • Rosemary J Korda3
  • Marjan Kljakovic4
  • Nicholas J Glasgow4

  • 1 Australian Primary Health Care Research Institute, Australian National University, Canberra, ACT.
  • 2 Menzies Centre for Health Policy, Australian National University, Canberra, ACT.
  • 3 National Centre for Epidemiology and Population Health and Australian Centre for Economic Research on Health, Australian National University, Canberra, ACT.
  • 4 Australian National University Medical School, Australian National University, Canberra, ACT.


Correspondence: laurann.yen@anu.edu.au

Acknowledgements: 

This research was carried out as part of the Serious and Continuing Illness Policy and Practice Study, with the support of an National Health and Medical Research Council program grant to the Menzies Centre for Health Policy. This research was completed using data collected through the 45 and Up Study (http://www.45andUp.org.au). The 45 and Up Study is managed by the Sax Institute in collaboration with major partner Cancer Council New South Wales and partners the National Heart Foundation (NSW Division); NSW Health; beyondblue: the national depression initiative; Ageing, Disability and Home Care, Department of Human Services NSW; and UnitingCare Ageing. We thank the many thousands of people participating in the 45 and Up Study.

Competing interests:

None relevant to this article declared (ICMJE disclosure forms completed).

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