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Erschienen in: European Journal of Clinical Microbiology & Infectious Diseases 2/2016

Open Access 01.02.2016 | Original Article

Increased health service use for asthma, but decreased for COPD: Northumbrian hospital episodes, 2013–2014

verfasst von: I. Shiue

Erschienen in: European Journal of Clinical Microbiology & Infectious Diseases | Ausgabe 2/2016

Abstract

The burden of respiratory disease has persisted over the years, for both men and women. The aim of the present study was to investigate the hospital episode rates in respiratory disease and to understand whether and how the use of the health service for respiratory disease might have changed in recent years in the North-East of England. Hospital episode data covering two full calendar years (in 2013–2014) was extracted from the Northumbria Healthcare NHS Foundation Trust, which serves a population of nearly half a million. Hospital episode rates were calculated from admissions divided by annual and small area-specific population size by sex and across age groups, presented with per 100,000 person-years. The use of the health service for influenza and pneumonia, acute lower respiratory infections and chronic obstructive pulmonary disease (COPD) increased with an advancing age, except for acute upper respiratory infections and asthma. Overall, the use of the health service for common respiratory diseases has seemed to be unchanged, except for asthma. There were large increases in young adults aged 20–50 for both men and women and the very old aged 90+ in women. Of note, there were large increases in acute lower respiratory infections for both men and women aged 90+, whereas there was also a large decrease in COPD in women aged 80–90. This is the first study to examine health service use for respiratory diseases by calculating the detailed population size as denominator. Re-diverting funding to improve population health on a yearly basis may serve the changing need in local areas.

Introduction

Evidence before this study

Respiratory disease, as an adult health condition, affects millions of people globally and is the one of the leading causes of health issues in both developed and developing countries [1]. Health service use has increased in older persons and costs millions of pounds in the UK, USA and several European countries, which could prompt considerations on long-term healthcare together with the entire socio-economic structure [25]. Hospital admissions have seemed to decrease in some regions, whereas in other regions primary care consultations seem to have increased, likely due to different study populations, study time periods and/or estimation methods in rates [628]. Continuously monitoring how people consume the health service because of various health conditions is important in assisting with individual, local and national health profiles and with the re-allocation of medical and social recourse effectively and consequently to prevent from unnecessary pain and spending. Therefore, such clinical evidence is necessary.

Knowledge gap

Investigating admission rates and hospitalisation rates could be perceived as a direct way of understanding how many patients are admitted and hospitalised require health service utilisation. Previous research tended to estimate age-standardised rates using the population census in a certain year by accommodating a specific population structure (e.g. Europe) or by adjusting for all ages in a specific study catchment to compare across countries and/or regions. However, looking at the total age-standardised rate by using the population census in a certain year may sometimes mislead and misguide the re-allocation of local medical and social resources, as one national, international or global policy does not always fit all owing to different unadjusted historical contexts (i.e. biological or non-biological risk contributor profiles).

Study aim

Following this context, therefore, the aim of the present study was to investigate the age-specific hospital episode rates in common respiratory diseases by sex and across age groups using an annual and small area-specific population size to understand and establish the monitoring on whether and how the use of the health service for respiratory diseases may have changed in recent years, if at all.

Materials and methods

Study sample

Hospital Episode Statistics (HES; more details via http://​www.​hscic.​gov.​uk/​hes) is a data warehouse containing details of all admissions, outpatient appointments and A&E attendances at National Health Service (NHS) hospitals in England. These data are collected during a patient's time at hospital and are submitted to allow hospitals to be paid for the care they deliver. HES data are designed to enable secondary use, particularly for non-clinical purposes. Each NHS trust in England collects its own patient data, and the anonymised data are kept locally within each trust and also centrally at the national level. Northumbria Healthcare NHS Foundation Trust (more details via https://​www.​northumbria.​nhs.​uk/​) covers the health service mostly for Northumberland and North Tyneside, including three major hospitals (Hexham General Hospital, North Tyneside General Hospital and Wansbeck General Hospital) and other smaller community hospitals (Alnwick Infirmary, Berwick Infirmary, Blyth Community Hospital, Haltwhistle War Memorial Hospital, Rothbury Community Hospital and Sir G B Hunter Memorial Hospital) facilitating health and social care and well-being for rehabilitation purposes (more details via http://​www.​nhs.​uk/​Services/​Trusts/​Overview/​DefaultView.​aspx?​id=​1802) and acts as a foundation trust that has been free from central government control since 2006 (more details via https://​www.​northumbria.​nhs.​uk/​about-us/​being-foundation-trust).

Variables and analyses

The data from the Northumbrian Hospital Episodes used in the present study covered two full calendar years (2013–2014). Health service use was determined by each admission coded as J00-06 Acute upper respiratory infections, J09-18 Influenza and pneumonia, J20-J22 Acute lower respiratory infections, G44 Other chronic obstructive pulmonary disease (COPD) and J45 Asthma, based on the International Classification of Diseases, 10th version (more details via http://​apps.​who.​int/​classifications/​icd10/​browse/​2015/​en; now re-directed to http://​apps.​who.​int/​classifications/​icd10/​browse/​2016/​en). To estimate the usage of the health service, age-specific HES rates were calculated from admissions divided by population size for each age group, presented with per 100,000 person-years. Estimates on population size in both 2013 and 2014 were obtained from the UK Office for National Statistics (more details via http://​www.​ons.​gov.​uk/​ons/​taxonomy/​index.​html?​nscl=​Population). Statistical software STATA version 13.0 (STATA, College Station, Texas, USA; more details via http://​www.​stata.​com/​) and Microsoft Excel (more details via https://​products.​office.​com/​en-us/​excel) were used to perform all the analyses and to generate graphs. As this was only a secondary data analysis with no individual identification in the present study, no further ethics approval was required.

Results

Figure 1 describes the population size by sex and across age groups in mid-2013 to mid-2014. Clearly, the population of young adults (aged 20–49) has decreased, whereas that of older adults (aged 50 and above) has increased. Figures 26 show the distribution of rates of health service use for acute upper respiratory infections, influenza and pneumonia, acute lower respiratory infections, COPD and asthma from 2013 to 2014 by sex and age groups respectively (also see Tables 15). Clearly, the use of the health service for influenza and pneumonia, acute lower respiratory infections and COPD increased with an advancing age in both men and women, but not for acute upper respiratory infections and asthma. Following these 2 years, the use of the health service for common respiratory diseases has seemed to be unchanged, except for asthma. There were large increases in young adults aged 20–50 for both men and women and the very old aged 90 and above in women. Of note, there were large increases in acute lower respiratory infections for both men and women aged 90 and above; there was also a large decrease in COPD in women aged 80–90.
Table 1
Hospital episode statistics for “J00–J06: acute upper respiratory infections”
2014
2013
All (years)
Episode
Population
2014 HES rate
All age groups (years)
Episode
Population
2013 HES rate
 0–9
775
55,577
1394.461738
0–9
802
55,550
1443.744374
 10–19
47
55,577
84.567357
10–19
30
56,221
53.36084381
 20–29
44
54,879
80.17638805
20–29
14
55,221
25.3526738
 30–39
30
58,734
51.07774032
30–39
14
58,955
23.74692562
 40–49
21
72,433
28.99231013
40–49
10
74,655
13.3949501
 50–59
27
77,070
35.0330868
50–59
16
75,724
21.12936453
 60–69
13
70,296
18.49322863
60–69
7
69,558
10.06354409
 70–79
14
45,482
30.78140803
70–79
11
44,044
24.97502498
 80–89
6
23,764
25.2482747
80–89
13
23,324
55.73658035
 90+
9
4,919
182.9640171
90+
8
4,716
169.6352841
 Total
164
40,7577
40.23779556
Total
93
406,197
22.89529465
Female (years)
 0–9
309
26,728
1156.090991
0–9
327
26767
1221.653529
 10–19
32
26,938
118.7912985
10–19
19
27247
69.73244761
 20–29
30
27,406
109.4650806
20–29
6
27663
21.68962152
 30–39
17
30,170
56.34736493
30–39
11
30200
36.42384106
 40–49
14
37,372
37.4612009
40–49
5
38432
13.00999167
 50–59
22
39,723
55.38353095
50–59
11
38943
28.24641142
 60–69
7
36,233
19.31940496
60–69
4
35817
11.16788117
 70–79
8
24,226
33.02237266
70–79
7
23546
29.72904103
 80–89
5
14,148
35.3406842
80–89
5
14045
35.5998576
 90+
9
3,525
255.3191489
90+
6
3407
176.1080129
 Total
112
212,803
52.63083697
Total
55
212053
25.936912
Male (years)
 0–9
466
28,849
1615.30729
0–9
475
28,783
1650.279679
 10–19
15
28,609
52.43105317
10–19
11
28,558
38.51810351
 20–29
14
27,473
50.9591235
20–29
8
27,558
29.02968285
 30–39
13
28,564
45.51183308
30–39
3
28,755
10.43296818
 40–49
7
35,061
19.9652035
40–49
5
36,223
13.80338459
 50–59
5
37,347
13.38795619
50–59
5
36,781
13.59397515
 60–69
6
34,063
17.61442034
60–69
3
33,741
8.891259892
 70–79
6
21,256
28.22732405
70–79
4
20,498
19.51409894
 80–89
1
9,616
10.39933444
80–89
8
9,279
86.21618709
 90+
0
1,394
0
90+
2
1,309
152.7883881
 Total
52
194,774
26.69760851
Total
38
194,144
19.57310038
Table 2
Hospital episode statistics for “J09–J18: influenza and pneumonia”
2014
2013
All (years)
Episode
Population
2014 HES rate
All age groups (years)
Episode
Population
2013 HES rate
 0–9
67
55,577
120.5534664
0–9
66
55,550
118.8118812
 10–19
26
55,577
46.78194217
10–19
16
56,221
28.4591167
 20–29
41
54,879
74.70981614
20–29
31
55,221
56.13806342
 30–39
73
58,734
124.2891681
30–39
75
58,955
127.215673
 40–49
147
72,433
202.9461709
40–49
147
74,655
196.9057665
 50–59
312
77,070
404.8267808
50–59
272
75,724
359.1991971
 60–69
620
70,296
881.9847502
60–69
600
69,558
862.5894937
 70–79
1,069
45,482
2,350.38037
70–79
868
44,044
1,970.756516
 80–89
1,494
23,764
6,286.820401
80–89
1,420
23,324
6,088.149546
 90+
625
4,919
12,705.83452
90+
561
4,716
11,895.6743
 Total
4,474
407,577
1,097.706691
Total
4,056
406, 197
998.5302698
Female (years)
 0–9
28
26,728
104.7590542
0–9
27
26,767
100.8704748
 10–19
10
26,938
37.12228079
10–19
9
27,247
33.03115939
 20–29
25
27,406
91.22090053
20–29
24
27,663
86.75848606
 30–39
46
30,170
152.4693404
30–39
29
30,200
96.02649007
 40–49
76
37,372
203.3608049
40–49
80
38,432
208.1598668
 50–59
156
39,723
392.7195831
50–59
141
38,943
362.0676373
 60–69
300
36,233
827.9744984
60–69
300
35,817
837.591088
 70–79
482
24,226
1,989.597953
70–79
398
23,546
1,690.308333
 80–89
750
14,148
5,301.102629
80–89
780
14,045
5,553.577786
 90+
391
3,525
11,092.19858
90+
333
3,407
9,773.994717
 Total
2,264
212,803
1,063.894776
Total
2,121
212,053
1,000.221643
Male (years)
 0–9
39
28,849
135.1866616
0–9
39
28,783
135.4966473
 10–19
16
28,609
55.92645671
10–19
7
28,558
24.51152041
 20–29
16
27,473
58.23899829
20–29
7
27,558
25.40097249
 30–39
27
28,564
94.52457639
30–39
46
28,755
159.9721788
 40–49
71
35,061
202.504207
40–49
67
36,223
184.9653535
 50–59
156
37,347
417.7042333
50–59
131
36,781
356.1621489
 60–69
320
34,063
939.4357514
60–69
300
33,741
889.1259892
 70–79
587
21,256
2,761.573203
70–79
470
20,498
2,292.906625
 80–89
744
9,616
7,737.104825
80–89
640
9,279
6,897.294967
 90+
234
1,394
16,786.22669
90+
228
1,309
17,417.87624
 Total
2,210
194,774
1,134.648362
total
1,935
194,144
996.6828746
Table 3
Hospital episode statistics for “J20–J22: other acute lower respiratory infections”
2014
2013
All (years)
Episode
Population
2014 HES rate
All age groups (years)
Episode
Population
2013 HES rate
 0–9
436
55,577
784.4971841
0–9
372
55,550
669.6669667
 10–19
10
55,577
17.99305468
10–19
9
56,221
16.00825314
 20–29
40
54,879
72.8876255
20–29
10
55,221
18.10905272
 30–39
48
58,734
81.72438451
30–39
28
58,955
47.49385124
 40–49
83
72,433
114.5886543
40–49
49
74,655
65.63525551
 50–59
105
77,070
136.239782
50–59
102
75,724
134.6996989
 60–69
180
70,296
256.0600888
60–69
134
69,558
192.6449869
 70–79
304
45,482
668.3962886
70–79
229
44,044
519.9346108
 80–89
339
23,764
1,426.527521
80–89
359
23,324
1,539.187103
 90+
188
4,919
3,821.915023
90+
138
4,716
2,926.208651
 Total
1,733
407,577
425.1957299
Total
1,430
406,197
352.0459285
Female (years)
 0–9
186
26,728
695.8994313
0–9
153
26,767
571.5993574
 10–19
3
26,938
11.13668424
10–19
3
27,247
11.01038646
 20–29
23
27,406
83.92322849
20–29
8
27,663
28.91949535
 30–39
27
30,170
89.49287372
30–39
21
30,200
69.53642384
 40–49
46
37,372
123.086803
40–49
22
38,432
57.24396336
 50–59
63
39,723
158.5982932
50–59
50
38,943
128.3927792
 60–69
65
36,233
179.3944747
60–69
46
35,817
128.4306335
 70–79
129
24,226
532.4857591
70–79
114
23,546
484.1586681
 80–89
190
14,148
1,342.945999
80–89
211
14,045
1,502.313991
 90+
148
3,525
4,198.58156
90+
108
3,407
3,169.944232
 Total
880
212,803
413.5280048
Total
736
212,053
347.0830406
Male (years)
 0–9
250
28,849
866.581164
0–9
219
28,783
760.8657888
 10–19
7
28,609
24.46782481
10–19
6
28,558
21.00987464
 20–29
17
27,473
61.87893568
20–29
2
27,558
7.257420713
 30–39
21
28,564
73.51911497
30–39
7
28,755
24.34359242
 40–49
37
35,061
105.5303614
40–49
27
36,223
74.53827679
 50–59
42
37,347
112.458832
50–59
52
36,781
141.3773416
 60–69
115
34,063
337.6097232
60–69
88
33,741
260.8102902
 70–79
175
21,256
823.2969514
70–79
115
20,498
561.0303444
 80–89
149
9,616
1,549.500832
80–89
148
9,279
1,594.999461
 90+
40
1,394
2,869.440459
90+
30
1,309
2,291.825821
 Total
853
194,774
437.9434627
Total
694
194,144
357.4666227
Table 4
Hospital episode statistics for “J44: COPD” (chronic obstructive pulmonary disease)
2014
2013
All (years)
Episode
Population
2014 HES rate
All
Episode
Population
2013 HES rate
 0–9
1
55,577
1.799305468
0–9
0
55,550
0
 10–19
0
55,577
0
10–19
0
56,221
0
 20–29
0
54,879
0
20–29
2
55,221
3.621810543
 30–39
6
58,734
10.21554806
30–39
1
58,955
1.696208973
 40–49
35
72,433
48.32051689
40–49
30
74,655
40.18485031
 50–59
245
77,070
317.8928247
50–59
255
75,724
336.7492473
 60–69
670
70,296
953.1125526
60–69
598
69,558
859.7141953
 70–79
930
45,482
2,044.764962
70–79
902
44,044
2,047.952048
 80–89
656
23,764
2,760.478034
80–89
722
23,324
3,095.523924
 90+
114
4,919
2,317.544216
90+
108
4,716
2,290.076336
 Total
2,657
407,577
651.9013585
Total
2,618
406,197
644.5148536
Female (years)
 0–9
0
26,728
0
0–9
0
26,767
0
 10–19
0
26,938
0
10–19
0
27,247
0
 20–29
0
27,406
0
20–29
0
27,663
0
 30–39
4
30,170
13.25820351
30–39
2
30,200
6.622516556
 40–49
20
37,372
53.51600128
40–49
21
38,432
54.64196503
 50–59
136
39,723
342.3709186
50–59
127
38,943
326.1176591
 60–69
342
36,233
943.8909282
60–69
304
35,817
848.7589692
 70–79
521
24,226
2,150.582019
70–79
493
23,546
2,093.773889
 80–89
385
14,148
2,721.232683
80–89
471
14,045
3,353.506586
 90+
60
3,525
1,702.12766
90+
56
3,407
1,643.674787
 Total
1,468
212,803
689.8398989
Total
1,474
212,053
695.1092416
Male (years)
 0–9
1
28,849
3.466324656
0–9
0
28,783
0
 10–19
0
28,609
0
10–19
0
28,558
0
 20–29
0
27,473
0
20–29
2
27,558
7.257420713
 30–39
2
28,564
7.001820473
30–39
0
28,755
0
 40–49
15
35,061
42.78257893
40–49
9
36,223
24.84609226
 50–59
109
37,347
291.857445
50–59
128
36,781
348.0057638
 60–69
328
34,063
962.9216452
60–69
294
33,741
871.3434694
 70–79
409
21,256
1924.162589
70–79
409
20,498
1,995.316616
 80–89
271
9,616
2818.219634
80–89
251
9,279
2,705.03287
 90+
54
1,394
3873.74462
90+
52
1,309
3,972.49809
 Total
1,189
194,774
610.4510869
Total
1,145
194,144
589.7684193
Table 5
Hospital episode statistics for “J45: asthma”
2014
2013
All (years)
Episode
Population
2014 HES rate
All
Episode
Population
2013 HES rate
 0–9
99
55,577
178.1312413
0–9
100
55,550
180.0180018
 10–19
58
55,577
104.3597171
10–19
48
56,221
85.3773501
 20–29
99
54,879
180.3968731
20–29
35
55,221
63.3816845
 30–39
91
58,734
154.9358123
30–39
60
58,955
101.7725384
 40–49
105
72,433
144.9615507
40–49
83
74,655
111.1780859
 50–59
88
77,070
114.1819125
50–59
70
75,724
92.44096984
 60–69
70
70,296
99.57892341
60–69
73
69,558
104.9483884
 70–79
59
45,482
129.7216481
70–79
56
44,044
127.1455817
 80–89
47
23,764
197.7781518
80–89
47
23,324
201.5091751
 90+
26
4,919
528.562716
90+
17
4,716
360.4749788
 Total
742
407,577
182.0514897
Total
589
406,197
145.0035328
Female (years)
 0–9
38
26,728
142.1730021
0–9
24
26,767
89.6626443
 10–19
30
26,938
111.3668424
10–19
26
27,247
95.42334936
 20–29
61
27,406
222.5789973
20–29
24
27,663
86.75848606
 30–39
74
30,170
245.276765
30–39
41
30,200
135.7615894
 40–49
74
37,372
198.0092048
40–49
67
38,432
174.3338884
 50–59
70
39,723
176.2203258
50–59
52
38,943
133.5284904
 60–69
44
36,233
121.4362598
60–69
53
35,817
147.9744256
 70–79
44
24,226
181.6230496
70–79
38
23,546
161.3862227
 80–89
34
14,148
240.3166525
80–89
42
14,045
299.0388038
 90+
24
3,525
680.8510638
90+
15
3,407
440.2700323
 Total
493
212,803
231.6696663
Total
382
212,053
180.1436433
Male (years)
 0–9
61
28,849
211.445804
0–9
76
28,783
264.0447486
 10–19
28
28,609
97.87129924
10–19
22
28,558
77.03620702
 20–29
38
27,473
138.3176209
20–29
11
27,558
39.91581392
 30–39
17
28,564
59.51547402
30–39
19
28,755
66.07546514
 40–49
31
35,061
88.4173298
40–49
16
36,223
44.17083069
 50–59
18
37,347
48.1966423
50–59
18
36,781
48.93831054
 60–69
26
34,063
76.3291548
60–69
20
33,741
59.27506594
 70–79
15
21,256
70.56831012
70–79
18
20,498
87.81344521
 80–89
13
9,616
135.1913478
80–89
5
9,279
53.88511693
 90+
2
1,394
143.472023
90+
2
1,309
152.7883881
 Total
249
194,774
127.8404715
Total
207
194,144
106.6218889

Discussion

Methodologically, there are a number of ways of examining hospital admissions, i.e. the use of the health service, in the population. To be specific, we could look historically at the trends by day of the week, by month, by season or by year. We could also examine geographically by hospital, by city, by region or by country. Mathematically, we could estimate by number, by rate or by standardisation. Politically, we could assess by practice, by policy or by reform. For example, respiratory admissions declined accompanying an increase in smoke-free areas or with the introduction of immunisation [2933]. Understanding the use of the health service in the bigger picture is critical for health service providers and policy makers to effectively re-allocate medical and social resources (from prevention to rehabilitation) respectively. The targeted at-risk population may shift following the change in investment in health and nursing programs and the subsequent risk contributor profile (biologically or non-biologically). Therefore, the performance review of such ought to be documented regularly, preferably annually.

Strengths and limitations

The present study has a few strengths. First, the data are from recent years. Therefore, the results provide information on recent health policy use. Second, the study period covers full calendar years. In addition, the population size was estimated on a yearly basis. Therefore, selection bias could be avoided in the presentation of trends and the estimation of rates could be more accurate than using the population census from a single year. However, mis-classification may not be completely avoidable [34, 35]. Third, this is the first HES study looking at the use of the health service in respiratory disease from the Northumbria area, which is free from central governmental control. However, there are also a few limitations that cannot be ignored. First, it was not possible to link with population surveys to understand patient risk contributor profiles, whether biological or non-biological. However, the entire study focus was to investigate if and how different age groups could present any change in health service use in recent years. Second, only two genders were identified. In other words, transgender was not properly coded. Therefore, no results on transgender people could be obtained (more details via http://​www.​ons.​gov.​uk/​ons/​about-ons/​business-transparency/​freedom-of-information/​what-can-i-request/​previous-foi-requests/​health-and-social-care/​transgender-population-figures/​index.​html). Third, some coding errors might not be 100% avoidable, which would affect the estimates. Taken together, future studies retaining the strengths and overcoming the limitations mentioned above to continuously monitor and document such clinical evidence from the local setting to the national setting would be recommended.

Research, practice and policy implications

From 2013 to 2014, there has been unchanged use of health service utilisation with regard to common respiratory diseases, except for asthma. Respiratory disease is a common condition that has a large and negative impact on quality of life and life expectancy, with high financial costs. To direct future research, local health policy and guidelines could benefit from annual clinical records on health service use for respiratory diseases. From the practice and policy perspectives, re-organising and re-diverting funding to improve population health on a yearly basis, including improving the role of health and nursing professionals in reducing the burden of rehabilitation and raising public awareness, attitude and knowledge may serve the changing need in local areas.

Compliance with ethical standards

Conflicts of interest

None.
Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

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Metadaten
Titel
Increased health service use for asthma, but decreased for COPD: Northumbrian hospital episodes, 2013–2014
verfasst von
I. Shiue
Publikationsdatum
01.02.2016
Verlag
Springer Berlin Heidelberg
Erschienen in
European Journal of Clinical Microbiology & Infectious Diseases / Ausgabe 2/2016
Print ISSN: 0934-9723
Elektronische ISSN: 1435-4373
DOI
https://doi.org/10.1007/s10096-015-2547-y

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