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Patient-specific versus Organisational Barriers to Program Adherence: A Multivariate Analysis Cover

Patient-specific versus Organisational Barriers to Program Adherence: A Multivariate Analysis

Open Access
|Mar 2019

Figures & Tables

Table 1

Eligibility criteria for the post-discharge follow-up program, Region Zealand, 2014. Patients who were not discharged to an intermediate care facility, with at least 3 of the below listed readmission risk factors, who were additionally clinically assessed to be eligible, were referred to the program.

Suspected cognitive disturbance or problems
Substance abuse that influences functional level
Psychiatric disease that influences functional level
Disadvantaged social network
Large loss in ability to carry out the activities of daily living
Malnutrition
Severe chronic, progressive, somatic or psychiatric disease
Six or more prescription drugs
High need for coordination of treatment and care
Acute hospital contact within the previous 6 month
Inconvenient residential facilities
Increased municipal services
The patient was not in contact with municipal services
History of fall
Clinical assessment (mandatory)
Figure 1

Adherence measures related to the post-discharge follow-up program and potential factors affecting adherence.

* Variables not analysed in relation to adherence step 1.

** Variables not analysed in step 2.

Figure 2

Patient flowchart, describing the patient cohort and different levels of analysis.

Table 2

Analysis of adherence step 1; factors related to referral from hospital to municipal setting. The middle columns show results from logistic regression model adjusted for age and gender, and the right hand columns show results of the full logistic regression model (n = 1659 patients).

FactorValueAbsolute numbers (%)Each variable adjusted for age and genderFull model analysis
OR (CI)P-valueOR (CI)P-value
Demographic
Age40–64 years59 (4)0.70 (0.40–1.20)0.540.66 (0.38–1.17)0.42
median = 84 years65–77 years369 (22)0.98 (0.75–1.27)1.03 (0.79–1.35)
78–89 years960 (58)11
90–102 years271 (16)1.08 (0.80–1.45)0.87 (0.63–1.20)
GenderMale676 (41)10.6910.56
Female983 (59)0.96 (0.77–1.19)0.93 (0.73–1.18)
Social
EducationHigher education190 (12)10.9010.71
Vocational education474 (29)0.92 (0.64–1.33)0.87 (0.59–1.27)
Primary school889 (54)0.96 (0.68–1.35)0.87 (0.61–1.23)
Missing: 106 (6)
Children living close byNo633 (42)10.7910.87
Yes884 (58)1.03 (0.83–1.28)1.02 (0.82–1.28)
Missing: 2 (0)
Spouse with or without comorbiditySpouse with CCI* of 0–1408 (25)10.5710.69
Spouse with CCI* of 2+150 (9)0.96 (0.65–1.44)0.92 (0.61–1.39)
No spouse1101 (66)1.12 (0.86–1.46)1.08 (0.82–1.42)
Organisational
HospitalHospital 1 (south-west)110 (7)0.42 (0.25–0.72)<0.00010.43 (0.25–0.74)<0.0001
Hospital 5 (north-east)117 (7)0.54 (0.32–0.91)0.60 (0.35–1.05)
Hospital 6 (mid-east)326 (20)0.61 (0.39–0.95)0.68 (0.43–1.07)
Hospital 3 (south)122 (7)11
Hospital 2 (north-west)326 (20)1.46 (0.92–2.31)1.57 (0.97–2.52)
Hospital 4 (mid-west)658 (40)1.50 (0.98–2.29)1.58 (1.02–2.45)
Received municipal homecare prior to admission?No770 (46)10.000210.01
Yes889 (54)1.50 (1.21–1.86)1.37 (1.10–1.70)
Health related
Main diagnosisOther diagnosis1199 (72)10.0410.13
Atypical symptoms460 (28)1.28 (1.01–1.62)1.22 (0.95–1.53)
Charlson comorbidity index score0–1663 (40)10.1610.08
2–3591 (36)1.18 (0.92–1.51)1.19 (0.92–1.54)
4+405 (24)0.91 (0.70–1.19)0.86 (0.64–1.56)
Previous hospitalization within 3-month periodNo813 (49)10.4010.72
Yes846 (51)0.91 (0.74–1.13)0.96 (0.74–1.20)
PolypharmacyNo528 (32)10.6110.68
Yes1131 (68)1.06 (0.85–1.32)1.05 (0.83–0.83)

[i] * CCI = Charlson Comorbidity Index Score.

Figure 3

Organisational factors. In the top; adjusted odds ratio plots with 95% confidence intervals for successful referral from hospital to municipality (step 1, full model) stratified by hospitals and for receiving post-discharge follow-up visits. Below; adjusted odds ratio plots with 95% confidence intervals for successfully completed post-discharge follow-up visits (step 2, full model) stratified by municipality. Note that municipality no. 372 is not represented in this figure due to the low number of observations (6 observations) and very broad 95% confidence interval.

Table 3

Analysis of adherence, step 2; factors related to odds of receiving post-discharge follow-up visits. The middle columns display results from logistic regression model adjusted for age and gender, and the right-hand columns show results of the full logistic regression model (n = 956 patients).

FactorValueAbsolute numbers (%)Each variable adjusted for age and genderFull model analysis
OR (CI)P-valueOR (CI)P-value
Demographic
Age40–64 years26 (3)0.76 (0.34–1.69)0.120.59 (0.25–1.42)0.07
median = 84 years65–77 years213 (22)1.38 (0.999–1.91)1.33 (0.94–1.89)
78–89 years549 (57)11
90–102 years168 (18)0.89 (0.63–1.26)0.77 (0.53–1.13)
GenderMale562 (59)10.0110.01
Female394 (41)1.42 (1.09–1.84)1.55 (1.14–2.10)
Social
EducationHigher education110 (12)10.8310.46
Vocational education271 (28)1.07 (1.68–1.68)1.10 (0.64–1.78)
Basic school517 (54)0.98 (0.64–1.48)0.90 (0.58–1.41)
Missing: 58 (6)
Children living close byNo405 (42)10.8310.82
Yes551 (58)1.03 (0.79–1.34)103 (0.78–1.34)
Spouse with or without comorbidity (based on Charlson Comorbidity Index/CCI)Spouse with CCI* of 0–1231 (24)10.7610.47
Spouse with CCI* of 2+83 (9)1.12 (0.67–1.85)1.15 (0.67–1.98)
No spouse642 (67)1.13 (0.81–1.57)1.25 (0.88)
Organisational
MunicipalityMunicipality no. 39019 (2)0.18 (0.05–0.66)<0.00010.20 (0.05–0.77)<0.0001
Municipality no. 26565 (7)0.33 (0.16–0.66)0.34 (0.16–0.69)
Municipality no. 25930 (3)0.43 (0.18–1.06)0.42 (0.17–1.05)
Municipality no. 33619 (2)0.59 (0.21–1.67)0.54 (0.19–1.53)
Municipality no. 32035 (4)0.86 (0.39–1.90)0.84 (0.37–1.88)
Municipality no. 30650 (5)0.98 (0.49–1.99)0.94 (0.46–1.93)
Municipality no. 31688 (9)11
Municipality no. 37040 (4)1.02 (0.48–2.18)0.96 (0.44–2.08)
Municipality no. 32967 (7)1.13 (059–2.15)1.15 (0.60–2.23)
Municipality no. 35031 (3)1.31 (0.57–3.00)1.35 (0.58–3.13)
Municipality no. 25331 (3)1.18 (0.51–2.71)1.40 (0.59–3.32)
Municipality no. 36050 (5)1.35 (0.66–2.74)1.43 (0.68–2.94)
Municipality no. 26916 (2)1.58 (0.52–4.79)1.68 (0.54–5.18)
Municipality no. 32678 (8)1.84 (0.98–345)1.89 (0.996–3.58)
Municipality no. 330250 (26)1.89 (1.15–3.12)1.96 (1.18–3.26)
Municipality no. 34081 (8)2.20 (1.17–4.15)2.11 (1.11–4.00)
Municipality no. 3766 (1)6.53 (0.73–58.79)7.02 (0.75–65.80)
Distance to general practitioner (n = 830 patients)0–4205 m631 (66)10.30
4206–15000 m169 (18)0.85 (0.61–1.20)nana
15000 + m30 (3)0.60 (0.28–1.27)nana
Missing: 126 (13)
Contact with general practitioner within one month prior to index admissionNo183 (19)10.0710.19
Yes773 (81)0.73 (0.53–1.03)0.78 (0.54–1.13)
Type of general practitionerShared656 (69)10.020.04
Solo300 (31)0.71 (0.54–0.94)0.73 (0.54–0.98)
Contact with emergency doctor within one month prior to index admissionNo607 (63)10.5410.58
Yes349 (37)0.92 (0.71–1.20)0.92 (0.69–1.23)
Received municipal homecare prior to admission?No405 (42)10.9710.56
Yes551 (58)1.00 (0.77–1.29)0.92 (0.69–1.22)
Health related
Main diagnosisOther diagnosis662 (69)10.6610.85
Atypical symptoms294 (31)1.06 (0.81–1.41)0.97 (0.71–1.32)
Charlson comorbidity index score0–1386 (40)10.3810.40
2–3356 (37)1.19 (0.89–1.60)1.23 (0.90–1.68)
4+214 (22)1.23 (0.87–1.74)1.22 (0.83–1.79)
Previous hospitalization within 3-month periodNo489 (51)10.5110.78
Yes467 (49)0.92 (0.71–1.19)0.96 (0.72–1.23)
PolypharmacyNo307 (32)10.9310.99
Yes649 (68)0.99 (0.75–1.30)1.00 (0.74–1.34)

[i] * CCI = Charlson Comorbidity Index Score.

DOI: https://doi.org/10.5334/ijic.4212 | Journal eISSN: 1568-4156
Language: English
Submitted on: Aug 28, 2018
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Accepted on: Feb 13, 2019
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Published on: Mar 15, 2019
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2019 Sara Fokdal Lehn, Ann-Dorthe Zwisler, Solvejg Gram Henneberg Pedersen, Thomas Gjørup, Lau Caspar Thygesen, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.