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/lp/ou_press/importance-of-comorbidities-in-the-treatment-of-primary-care-patients-gVnIklvqEU
- Publisher
- Oxford University Press
- Copyright
- © The Author(s) 2018. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
- ISSN
- 0263-2136
- eISSN
- 1460-2229
- DOI
- 10.1093/fampra/cmx135
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- See Article on Publisher Site
Abstract
Abstract Background Both non-cardiac and cardiac comorbidities are related to the prognosis of chronic heart failure (HF), but so far little is known about the impact of comorbidities on treatment difficulties in routine care. Objectives To investigate which comorbidities are associated with treatment difficulties in primary care. We hypothesized that somatic comorbidities as well as psychosocial distress are associated with treatment difficulties. Methods In this baseline analysis of data of the observational RECODE-HF study, HF patients were recruited via primary care practices in two German sites. They received a questionnaire by mail to measure psychosocial distress. Each patient’s GP was interviewed by phone regarding the patient’s comorbidities and treatment difficulties. Logistic regression analyses controlled for GP cluster effects were calculated to investigate the association between comorbidities/psychosocial distress and treatment difficulties. Results The 3282 patients of 285 GPs included in the analysis were aged 74.2 (±10.1) years and had a mean number of 4.6 (±2.4) comorbidities. GPs reported treatment difficulties in 32.5% of the patients. Allergies/drug intolerance [odds ratio (ORs)=2.0], asthma/chronic obstructive pulmonary disease (ORs=1.4), renal insufficiency (ORs=1.3), atherosclerosis/peripheral arterial occlusive disease (ORs=1.3) and cardiac arrhythmias (ORs=1.2) as well as patient-reported psychosocial distress (ORs=1.2), HF severity (ORs=3.7–1.6) and age (ORs=0.98) were associated with treatment difficulties. Conclusion Five somatic comorbidity groups as well as patient-reported psychosocial distress were significantly associated with a higher risk of GP-reported treatment difficulties. Further efforts to address comorbidities in clinical guidelines could be built on these results. Anxiety, comorbidity, depression, health services research, heart failure, primary health care Introduction Nearly 40% of patients with heart failure (HF) have five or more comorbidities (1) and HF patients cared for by GPs have been shown to have more comorbidities than HF patients cared for by cardiologists (2). In patients with chronic HF, both non-cardiac and cardiac comorbidities are related to hospitalization frequency, disease progression, and to the prognosis of HF (1,3,4). Furthermore, psychological disorders like anxiety and depression were shown to be associated with the HF prognosis, even though evidence for depression was stronger than evidence for anxiety (5). Comorbidities were frequently reported to complicate the care for patients with HF (6). The handling of comorbidities is unclear, because the established treatments of comorbidities in HF patients did not show the expected effects, which was true for somatic as well as psychologic disorders like depression (7). So far, comorbidities in HF have been investigated with regard to their prognostic relevance, e.g. by Braunstein et al. (1),or in a hospital setting (8) but studies neglected the impact of comorbidities on treatment difficulties in primary routine care. Only one qualitative study investigated the HF patient’s view on treatment difficulties in general practice compared to HF clinics (9), without the focus on comorbidities. The aim of this study was to determine which comorbidities were associated with GP-reported treatment difficulties. We hypothesize that somatic disorders as well as psychosocial distress are significantly associated with perceived treatment difficulties in patients with HF in general practice. Methods In this observational study, patients with HF were recruited between February 2012 and June 2014 via primary care practices in two German study sites. Data were collected between August 2012 and November 2014. The study design has been described in the study protocol (10). The main focus of the longitudinal study lied on psychosocial distress. Therefore, patients with psychosocial distress were included prioritized in the study (see section Psychosocial distress). This is a cross-sectional investigation of the baseline data. Data ascertainment First, all GPs at the two study sites including surrounding areas were invited to take part in the study. In the surgeries of the participating GPs, patients were selected from the practice software. The inclusion criteria were diagnosis of HF within the last 5 years, at least one contact with the GP within the last 6 months and aged at least 18 years. Patients who were no regular patient of the participating practice or who passed away since their last GP consultation were excluded. Furthermore, patients with dementia were excluded because they may not be able to give valid information in the self-administered questionnaire. All eligible patients received a personal letter from their GP with an invitation to participate in the study along with study material. Those patients who were willing to participate returned the informed, written letters of consent to the study centre. In turn, they received a self-administered baseline questionnaire by mail and sent it back to the study centre. Besides instruments to measure symptoms of anxiety and depression (see below for further detail), the questionnaire contained questions regarding sociodemographics and education (CASMIN criteria (11)). Due to the study design, all incoming patient questionnaires were screened for psychosocial distress by a hierarchical algorithm (12) (see Psychosocial distress section). According to the study protocol (10), a higher ratio of patients with psychosocial distress were included in the study (all patients with psychosocial distress, and 80% randomly selected patients of those without psychosocial distress). Then, the GP of each included patient was interviewed by phone regarding his/her patient’s New York Heart Association (NYHA) classification, somatic and psychologic disorders and potential treatment difficulties. Psychosocial distress The algorithm to screen for psychosocial distress (12) is based on the Patient Health Questionnaire Depression Scale (PHQ-9, 13), Hospital Anxiety and Depression Scale (14,15) subscales depression (HADS-D) and anxiety (HADS-A) and selected items of the PROMIS Anxiety Scale (PROMIS Anxiety (16,17)). In brief, all patients with PHQ-9 score of >8 and HADS-D score of >8 as well as those patients with PROMIS Anxiety score of >18 were defined as displaying psychosocial distress. Even though the algorithm was established to identify patients with depression/adjustment disorder and anxiety disorder, the positive predictive values do not allow an immediate diagnosis of a depressive/adjustment or anxiety disorder (12). Therefore, psychosocial distress was defined as showing symptoms of depression/adjustment disorder and/or anxiety. Comorbidities and treatment difficulties In the telephonic interview, the comorbidities were assessed by asking if the patient had any conditions of the Charlson Comorbidity Index (18), followed by the request to disclose all further acute and chronic illnesses which the patient currently had using three-digit ICD-10 codes. In a next step, all conditions of the Charlson Index were transformed into three-digit ICD-10 codes. Then, the ICD-10 codes from both sources (Charlson Index and the ICD-10 codes of acute and chronic illnesses named by the GP) were sorted into 42 comorbidity groups based on an established list of relevant chronic conditions in ambulatory care (MultiCare list of chronic conditions) (19), which was adapted due to the inclusion and exclusion criteria of the current study, e.g. dementia was an exclusion criterion in this study. At the end of the interview, the GP was asked ‘What difficulties have you encountered when treating heart failure in this patient?’ The answer to this open question was coded into categories by the interviewer. The categories were pre-specified and were amended based on the GPs’ answers after the first interviews. The categories were not presented to the GPs. Data analysis Statistical analyses were performed using SPSS version 20 and 23. No data imputation strategies were applied. The nominal level of significance has been set at P = 0.05 for all analyses. Descriptive analyses were calculated to describe sample characteristics and the GP-reported treatment difficulties in the HF patients. t-Tests and chi-square tests were calculated to test for significant differences where appropriate. Bivariate logistic regression models with the outcome ‘any treatment difficulties (yes/no)’ were calculated for each of the 42 comorbidity groups. Then, a multivariable logistic regression model with the outcome ‘any treatment difficulties’ (yes/no) controlled for the random GP cluster effect was calculated by the procedure GENLIN-MIXED. All comorbidity groups showing a significant association with treatment difficulties in the bivariate analyses as well as the number of comorbidities (MultiCare list), age, gender, education, NYHA classification and psychosocial distress were included in the multivariable logistic regression model. Odds ratios and 95% confidence intervals were calculated. Methods to reduce bias Due to the study design, the cohort is not representative regarding the prevalence of psychosocial distress as identified by the patient questionnaire. To address this bias, psychosocial distress is included in the multivariable analyses to control for its effect. Furthermore, the frequencies of treatment difficulties were additionally provided stratified by psychosocial distress. Ethical approval The study was conducted in compliance with the Declaration of Helsinki and adheres to the Belmont principles. The study was approved by the local ethics committees (Medical Association of Hamburg, Approval No. PV3889; Ethics Committee of the Medical Faculty of the University of Würzburg, Approval No. 125/12, Ethics Committee at the University of Göttingen Medical Center, Approval No. 19/8/11). All study participants gave written informed consent before participating in the study. Results Of the 4220 GPs invited to take part in the study, 293 were willing to participate (6.6%). A total of 13830 patients were identified in the praxis software and invited to participate by their GPs. Of those invited, 5385 (38.9%) consented to participate in the study and 4909 (35.5%) sent back a baseline questionnaire. A total number of 3821 telephonic interviews were conducted and finally 3387 patients met the inclusion criteria of the study. A flow chart with detailed information has been provided earlier (12). Sample characteristics Of all 3387 patients included in the study, 105 patients without valid information on treatment difficulties had to be excluded from the analysis. Thus, 3282 HF patients with valid information on presence or absence of GP-reported treatment difficulties from 285 interviewed GPs were included in the analysis. Sample characteristics are presented in Table 1. Table 1. Sample characteristics of heart failure patients (2012–2014) Patients without GP-reported treatment difficulties Patients with GP-reported treatment difficulties Total sample Differences between groups (P) Total valid n* Age, mean (SD) 74.2 (10.1) 74.2 (10.2) 74.2 (10.1) 0.970 3093 Male gender, n (%) 1162 (53.5) 572 (54.4) 1734 (53.8) 0.660 3222 Education level, n (%) 0.674 3212 primary 1387 (64.2) 687 (65.4) 2074 (64.6) secondary 590 (27.3) 271 (25.8) 861 (26.8) tertiary 185 (8.6) 92 (8.8) 277 (8.6) NYHA classification, n (%) <0.001 3229 Class I 600 (27.5) 173 (16.5) 773 (23.9) Class II 1147 (52.6) 470 (44.8) 1617 (50.1) Class III 386 (17.7) 365 (34.8) 751 (23.3) Class IV 46 (2.1) 42 (4.0) 88 (2.7) Number of comorbidities (MultiCare list), mean (SD) 4.4 (2.3) 5.0 (2.6) 4.6 (2.4) <0.001 3220 Psychosocial distress, n (%) 597 (28.1) 351 (34.6) 948 (30.2) <0.001 3134 Total n (%) 2216 (67.5) 1066 (32.5) 3282 (100) Patients without GP-reported treatment difficulties Patients with GP-reported treatment difficulties Total sample Differences between groups (P) Total valid n* Age, mean (SD) 74.2 (10.1) 74.2 (10.2) 74.2 (10.1) 0.970 3093 Male gender, n (%) 1162 (53.5) 572 (54.4) 1734 (53.8) 0.660 3222 Education level, n (%) 0.674 3212 primary 1387 (64.2) 687 (65.4) 2074 (64.6) secondary 590 (27.3) 271 (25.8) 861 (26.8) tertiary 185 (8.6) 92 (8.8) 277 (8.6) NYHA classification, n (%) <0.001 3229 Class I 600 (27.5) 173 (16.5) 773 (23.9) Class II 1147 (52.6) 470 (44.8) 1617 (50.1) Class III 386 (17.7) 365 (34.8) 751 (23.3) Class IV 46 (2.1) 42 (4.0) 88 (2.7) Number of comorbidities (MultiCare list), mean (SD) 4.4 (2.3) 5.0 (2.6) 4.6 (2.4) <0.001 3220 Psychosocial distress, n (%) 597 (28.1) 351 (34.6) 948 (30.2) <0.001 3134 Total n (%) 2216 (67.5) 1066 (32.5) 3282 (100) NYHA, New York Heart Association; SD, standard deviation. *Number of patients with non-missing data. View Large Table 1. Sample characteristics of heart failure patients (2012–2014) Patients without GP-reported treatment difficulties Patients with GP-reported treatment difficulties Total sample Differences between groups (P) Total valid n* Age, mean (SD) 74.2 (10.1) 74.2 (10.2) 74.2 (10.1) 0.970 3093 Male gender, n (%) 1162 (53.5) 572 (54.4) 1734 (53.8) 0.660 3222 Education level, n (%) 0.674 3212 primary 1387 (64.2) 687 (65.4) 2074 (64.6) secondary 590 (27.3) 271 (25.8) 861 (26.8) tertiary 185 (8.6) 92 (8.8) 277 (8.6) NYHA classification, n (%) <0.001 3229 Class I 600 (27.5) 173 (16.5) 773 (23.9) Class II 1147 (52.6) 470 (44.8) 1617 (50.1) Class III 386 (17.7) 365 (34.8) 751 (23.3) Class IV 46 (2.1) 42 (4.0) 88 (2.7) Number of comorbidities (MultiCare list), mean (SD) 4.4 (2.3) 5.0 (2.6) 4.6 (2.4) <0.001 3220 Psychosocial distress, n (%) 597 (28.1) 351 (34.6) 948 (30.2) <0.001 3134 Total n (%) 2216 (67.5) 1066 (32.5) 3282 (100) Patients without GP-reported treatment difficulties Patients with GP-reported treatment difficulties Total sample Differences between groups (P) Total valid n* Age, mean (SD) 74.2 (10.1) 74.2 (10.2) 74.2 (10.1) 0.970 3093 Male gender, n (%) 1162 (53.5) 572 (54.4) 1734 (53.8) 0.660 3222 Education level, n (%) 0.674 3212 primary 1387 (64.2) 687 (65.4) 2074 (64.6) secondary 590 (27.3) 271 (25.8) 861 (26.8) tertiary 185 (8.6) 92 (8.8) 277 (8.6) NYHA classification, n (%) <0.001 3229 Class I 600 (27.5) 173 (16.5) 773 (23.9) Class II 1147 (52.6) 470 (44.8) 1617 (50.1) Class III 386 (17.7) 365 (34.8) 751 (23.3) Class IV 46 (2.1) 42 (4.0) 88 (2.7) Number of comorbidities (MultiCare list), mean (SD) 4.4 (2.3) 5.0 (2.6) 4.6 (2.4) <0.001 3220 Psychosocial distress, n (%) 597 (28.1) 351 (34.6) 948 (30.2) <0.001 3134 Total n (%) 2216 (67.5) 1066 (32.5) 3282 (100) NYHA, New York Heart Association; SD, standard deviation. *Number of patients with non-missing data. View Large Treatment difficulties The GP reported difficulties in treating the HF in 1066 (32.5%) of the 3282 patients. The most prevalent types of treatment difficulties were ‘interaction between HF treatment and comorbid disease/multimorbidity’ and ‘non-adherence’ (see Table 2). All treatment difficulties are also provided stratified by psychosocial distress to address the bias of overrepresentation of HF patients with psychosocial distress in this study (see Supplementary Table S1). Comorbidities Table 3 displays the results of the multivariable logistic regression analysis with the endpoint ‘treatment difficulties’. Four of the five comorbidity groups with a significant bivariate association with treatment difficulties remained significant in the multivariable model. Furthermore, psychosocial distress, advanced HF and age were significantly associated with treatment difficulties. The NYHA classification had the strongest association with GP-reported treatment difficulties, while gender, education and the number of comorbidities were not significantly associated with treatment difficulties. Table 3. Covariates of treatment difficulties reported by the GP (2012–2014) OR P 95% Confidence interval NYHA class III/IV (reference: Class I) 3.695 <0.001 2.784 4.904 NYHA class II (reference: Class I) 1.575 <0.001 1.229 2.019 Allergies/drug intolerance 2.012 0.009 1.192 3.396 Asthma/chronic obstructive pulmonary disease 1.362 0.003 1.112 1.669 Renal insufficiency 1.278 0.028 1.027 1.591 Atherosclerosis/peripheral arterial occlusive disease 1.270 0.048 1.002 1.609 Cardiac arrhythmias 1.238 0.041 1.009 1.520 Psychosocial distress 1.233 0.040 1.010 1.506 Chronic gastritis/gastroesophageal reflux disease 1.107 0.428 0.861 1.424 High education level (reference: low) 1.066 0.700 0.769 1.478 Medium education level (reference: low) 0.954 0.665 0.773 1.179 Number of comorbidities (MultiCare list) 1.027 0.307 0.976 1.082 Age 0.984 0.001 0.975 0.994 Male gender 0.856 0.109 0.708 1.035 Constant 0.548 0.121 0.256 1.171 OR P 95% Confidence interval NYHA class III/IV (reference: Class I) 3.695 <0.001 2.784 4.904 NYHA class II (reference: Class I) 1.575 <0.001 1.229 2.019 Allergies/drug intolerance 2.012 0.009 1.192 3.396 Asthma/chronic obstructive pulmonary disease 1.362 0.003 1.112 1.669 Renal insufficiency 1.278 0.028 1.027 1.591 Atherosclerosis/peripheral arterial occlusive disease 1.270 0.048 1.002 1.609 Cardiac arrhythmias 1.238 0.041 1.009 1.520 Psychosocial distress 1.233 0.040 1.010 1.506 Chronic gastritis/gastroesophageal reflux disease 1.107 0.428 0.861 1.424 High education level (reference: low) 1.066 0.700 0.769 1.478 Medium education level (reference: low) 0.954 0.665 0.773 1.179 Number of comorbidities (MultiCare list) 1.027 0.307 0.976 1.082 Age 0.984 0.001 0.975 0.994 Male gender 0.856 0.109 0.708 1.035 Constant 0.548 0.121 0.256 1.171 NYHA, New York Heart Association. Multivariable logistic regression with outcome any treatment difficulties controlled by GP cluster effect (Z = 6.587; P < 0.001); n = 2843; Overall correct classification 76.4%. Bold letters indicate significant associations. View Large Table 3. Covariates of treatment difficulties reported by the GP (2012–2014) OR P 95% Confidence interval NYHA class III/IV (reference: Class I) 3.695 <0.001 2.784 4.904 NYHA class II (reference: Class I) 1.575 <0.001 1.229 2.019 Allergies/drug intolerance 2.012 0.009 1.192 3.396 Asthma/chronic obstructive pulmonary disease 1.362 0.003 1.112 1.669 Renal insufficiency 1.278 0.028 1.027 1.591 Atherosclerosis/peripheral arterial occlusive disease 1.270 0.048 1.002 1.609 Cardiac arrhythmias 1.238 0.041 1.009 1.520 Psychosocial distress 1.233 0.040 1.010 1.506 Chronic gastritis/gastroesophageal reflux disease 1.107 0.428 0.861 1.424 High education level (reference: low) 1.066 0.700 0.769 1.478 Medium education level (reference: low) 0.954 0.665 0.773 1.179 Number of comorbidities (MultiCare list) 1.027 0.307 0.976 1.082 Age 0.984 0.001 0.975 0.994 Male gender 0.856 0.109 0.708 1.035 Constant 0.548 0.121 0.256 1.171 OR P 95% Confidence interval NYHA class III/IV (reference: Class I) 3.695 <0.001 2.784 4.904 NYHA class II (reference: Class I) 1.575 <0.001 1.229 2.019 Allergies/drug intolerance 2.012 0.009 1.192 3.396 Asthma/chronic obstructive pulmonary disease 1.362 0.003 1.112 1.669 Renal insufficiency 1.278 0.028 1.027 1.591 Atherosclerosis/peripheral arterial occlusive disease 1.270 0.048 1.002 1.609 Cardiac arrhythmias 1.238 0.041 1.009 1.520 Psychosocial distress 1.233 0.040 1.010 1.506 Chronic gastritis/gastroesophageal reflux disease 1.107 0.428 0.861 1.424 High education level (reference: low) 1.066 0.700 0.769 1.478 Medium education level (reference: low) 0.954 0.665 0.773 1.179 Number of comorbidities (MultiCare list) 1.027 0.307 0.976 1.082 Age 0.984 0.001 0.975 0.994 Male gender 0.856 0.109 0.708 1.035 Constant 0.548 0.121 0.256 1.171 NYHA, New York Heart Association. Multivariable logistic regression with outcome any treatment difficulties controlled by GP cluster effect (Z = 6.587; P < 0.001); n = 2843; Overall correct classification 76.4%. Bold letters indicate significant associations. View Large We once more calculated the frequency of types of the treatment difficulties (as listed in Table 2) stratified by the significant comorbidities of the multivariable model (allergies/drug intolerance, asthma/chronic obstructive pulmonary disease, renal insufficiency, atherosclerosis/peripheral arterial occlusive disease, cardiac arrhythmias and psychosocial distress). As in Table 2 shown for the full sample, ‘interaction between comorbid diseases and HF treatment’ was the most frequent cause for treatment difficulties in each of the comorbidities, followed by ‘non-adherence’. The only exception was the comorbidity group ‘allergies/drug intolerance’. Here, ‘side effects of medications/medication intolerance’ shared the first rank with ‘interaction between HF treatment and comorbid disease/multimorbidity’. All frequencies are shown in Table 4. Table 2. Types of treatment difficulties heart failure (HF) patients reported by the GP (2012–2014) Treatment difficulties differentiated by type (partly multiple) n = 3282 (100%) Interaction between HF treatment and comorbid disease/multimorbidity n (%) 384 (11.7) Non-adherence n (%) 346 (10.5) Side effects/drug intolerance n (%) 208 (6.3) Difficulties regarding HF diagnosis/treatment or severity of heart failure n (%) 104 (3.2) Adjustment of blood pressure n (%) 79 (2.4) Patient’s understanding of disease n (%) 35 (1.1) Difficult care situation at home n (%) 31 (0.9) Social problems n (%) 26 (0.8) Weight control n (%) 21 (0.6) Other n (%) 103 (3.1) Any treatment difficulties n (%) 1066 (32.5) Treatment difficulties differentiated by type (partly multiple) n = 3282 (100%) Interaction between HF treatment and comorbid disease/multimorbidity n (%) 384 (11.7) Non-adherence n (%) 346 (10.5) Side effects/drug intolerance n (%) 208 (6.3) Difficulties regarding HF diagnosis/treatment or severity of heart failure n (%) 104 (3.2) Adjustment of blood pressure n (%) 79 (2.4) Patient’s understanding of disease n (%) 35 (1.1) Difficult care situation at home n (%) 31 (0.9) Social problems n (%) 26 (0.8) Weight control n (%) 21 (0.6) Other n (%) 103 (3.1) Any treatment difficulties n (%) 1066 (32.5) View Large Table 2. Types of treatment difficulties heart failure (HF) patients reported by the GP (2012–2014) Treatment difficulties differentiated by type (partly multiple) n = 3282 (100%) Interaction between HF treatment and comorbid disease/multimorbidity n (%) 384 (11.7) Non-adherence n (%) 346 (10.5) Side effects/drug intolerance n (%) 208 (6.3) Difficulties regarding HF diagnosis/treatment or severity of heart failure n (%) 104 (3.2) Adjustment of blood pressure n (%) 79 (2.4) Patient’s understanding of disease n (%) 35 (1.1) Difficult care situation at home n (%) 31 (0.9) Social problems n (%) 26 (0.8) Weight control n (%) 21 (0.6) Other n (%) 103 (3.1) Any treatment difficulties n (%) 1066 (32.5) Treatment difficulties differentiated by type (partly multiple) n = 3282 (100%) Interaction between HF treatment and comorbid disease/multimorbidity n (%) 384 (11.7) Non-adherence n (%) 346 (10.5) Side effects/drug intolerance n (%) 208 (6.3) Difficulties regarding HF diagnosis/treatment or severity of heart failure n (%) 104 (3.2) Adjustment of blood pressure n (%) 79 (2.4) Patient’s understanding of disease n (%) 35 (1.1) Difficult care situation at home n (%) 31 (0.9) Social problems n (%) 26 (0.8) Weight control n (%) 21 (0.6) Other n (%) 103 (3.1) Any treatment difficulties n (%) 1066 (32.5) View Large Table 4. Types of treatment difficulties in heart failure (HF) patients reported by GP stratified by comorbidities (2012–2014) Allergies/drug intolerance n = 90 (100%) Asthma/chronic obstructive pulmonary disease n = 955 (100%) Renal insufficiency n = 943 (100%) Atherosclerosis/peripheral arterial occlusive disease n = 618 (100%) Cardiac arrhythmias n = 980 (100%) Heart failure patients with psychosocial distress n = 948 (100%) Interaction between HF treatment and comorbid disease/multimorbidity, n (%) 15 (16.7) 149 (15.6) 159 (16.9) 110 (17.8) 132 (13.5) 125 (13.2) Non-adherence, n (%) 6 (6.7) 130 (13.6) 105 (11.1) 90 (14.6) 103 (10.3) 114 (12.0) Side effects/intolerance of medication, n (%) 15 (16.7) 63 (6.6) 74 (7.8) 46 (7.4) 69 (7.0) 65 (6.9) Difficulties regarding HF diagnosis/treatment or severity of heart failure, n (%) 4 (4.4) 35 (3.8) 48 (5.1) 23 (3.7) 49 (5.0) 37 (3.9) Adjustment of blood pressure, n (%) 5 (5.6) 21 (2.2) 29 (3.1) 16 (2.6) 21 (2.1) 29 (3.1) Patient’s understanding of disease, n (%) 3 (3.3) 10 (1.0) 13 (1.4) 9 (1.5) 7 (0.7) 9 (0.9) Difficult care situation at home, n (%) 1 (1.1) 8 (0.8) 12 (1.3) 8 (1.3) 14 (1.4) 12 (1.3) Social problems, n (%) – 7 (0.7) 9 (1.0) 11 (1.8) 8 (0.8) 13 (1.4) Weight control, n (%) – 6 (0.6) 8 (0.8) 6 (1.0) 6 (0.6) 7 (0.7) Others, n (%) 5 (5.6) 43 (4.5) 31 (3.3) 21 (3.4) 43 (4.4) 28 (3.0) Any treatment difficulties, n (%) 38 (42.2) 380 (39.8) 387 (41.0) 254 (41.1) 364 (37.1) 351 (37.0) Allergies/drug intolerance n = 90 (100%) Asthma/chronic obstructive pulmonary disease n = 955 (100%) Renal insufficiency n = 943 (100%) Atherosclerosis/peripheral arterial occlusive disease n = 618 (100%) Cardiac arrhythmias n = 980 (100%) Heart failure patients with psychosocial distress n = 948 (100%) Interaction between HF treatment and comorbid disease/multimorbidity, n (%) 15 (16.7) 149 (15.6) 159 (16.9) 110 (17.8) 132 (13.5) 125 (13.2) Non-adherence, n (%) 6 (6.7) 130 (13.6) 105 (11.1) 90 (14.6) 103 (10.3) 114 (12.0) Side effects/intolerance of medication, n (%) 15 (16.7) 63 (6.6) 74 (7.8) 46 (7.4) 69 (7.0) 65 (6.9) Difficulties regarding HF diagnosis/treatment or severity of heart failure, n (%) 4 (4.4) 35 (3.8) 48 (5.1) 23 (3.7) 49 (5.0) 37 (3.9) Adjustment of blood pressure, n (%) 5 (5.6) 21 (2.2) 29 (3.1) 16 (2.6) 21 (2.1) 29 (3.1) Patient’s understanding of disease, n (%) 3 (3.3) 10 (1.0) 13 (1.4) 9 (1.5) 7 (0.7) 9 (0.9) Difficult care situation at home, n (%) 1 (1.1) 8 (0.8) 12 (1.3) 8 (1.3) 14 (1.4) 12 (1.3) Social problems, n (%) – 7 (0.7) 9 (1.0) 11 (1.8) 8 (0.8) 13 (1.4) Weight control, n (%) – 6 (0.6) 8 (0.8) 6 (1.0) 6 (0.6) 7 (0.7) Others, n (%) 5 (5.6) 43 (4.5) 31 (3.3) 21 (3.4) 43 (4.4) 28 (3.0) Any treatment difficulties, n (%) 38 (42.2) 380 (39.8) 387 (41.0) 254 (41.1) 364 (37.1) 351 (37.0) View Large Table 4. Types of treatment difficulties in heart failure (HF) patients reported by GP stratified by comorbidities (2012–2014) Allergies/drug intolerance n = 90 (100%) Asthma/chronic obstructive pulmonary disease n = 955 (100%) Renal insufficiency n = 943 (100%) Atherosclerosis/peripheral arterial occlusive disease n = 618 (100%) Cardiac arrhythmias n = 980 (100%) Heart failure patients with psychosocial distress n = 948 (100%) Interaction between HF treatment and comorbid disease/multimorbidity, n (%) 15 (16.7) 149 (15.6) 159 (16.9) 110 (17.8) 132 (13.5) 125 (13.2) Non-adherence, n (%) 6 (6.7) 130 (13.6) 105 (11.1) 90 (14.6) 103 (10.3) 114 (12.0) Side effects/intolerance of medication, n (%) 15 (16.7) 63 (6.6) 74 (7.8) 46 (7.4) 69 (7.0) 65 (6.9) Difficulties regarding HF diagnosis/treatment or severity of heart failure, n (%) 4 (4.4) 35 (3.8) 48 (5.1) 23 (3.7) 49 (5.0) 37 (3.9) Adjustment of blood pressure, n (%) 5 (5.6) 21 (2.2) 29 (3.1) 16 (2.6) 21 (2.1) 29 (3.1) Patient’s understanding of disease, n (%) 3 (3.3) 10 (1.0) 13 (1.4) 9 (1.5) 7 (0.7) 9 (0.9) Difficult care situation at home, n (%) 1 (1.1) 8 (0.8) 12 (1.3) 8 (1.3) 14 (1.4) 12 (1.3) Social problems, n (%) – 7 (0.7) 9 (1.0) 11 (1.8) 8 (0.8) 13 (1.4) Weight control, n (%) – 6 (0.6) 8 (0.8) 6 (1.0) 6 (0.6) 7 (0.7) Others, n (%) 5 (5.6) 43 (4.5) 31 (3.3) 21 (3.4) 43 (4.4) 28 (3.0) Any treatment difficulties, n (%) 38 (42.2) 380 (39.8) 387 (41.0) 254 (41.1) 364 (37.1) 351 (37.0) Allergies/drug intolerance n = 90 (100%) Asthma/chronic obstructive pulmonary disease n = 955 (100%) Renal insufficiency n = 943 (100%) Atherosclerosis/peripheral arterial occlusive disease n = 618 (100%) Cardiac arrhythmias n = 980 (100%) Heart failure patients with psychosocial distress n = 948 (100%) Interaction between HF treatment and comorbid disease/multimorbidity, n (%) 15 (16.7) 149 (15.6) 159 (16.9) 110 (17.8) 132 (13.5) 125 (13.2) Non-adherence, n (%) 6 (6.7) 130 (13.6) 105 (11.1) 90 (14.6) 103 (10.3) 114 (12.0) Side effects/intolerance of medication, n (%) 15 (16.7) 63 (6.6) 74 (7.8) 46 (7.4) 69 (7.0) 65 (6.9) Difficulties regarding HF diagnosis/treatment or severity of heart failure, n (%) 4 (4.4) 35 (3.8) 48 (5.1) 23 (3.7) 49 (5.0) 37 (3.9) Adjustment of blood pressure, n (%) 5 (5.6) 21 (2.2) 29 (3.1) 16 (2.6) 21 (2.1) 29 (3.1) Patient’s understanding of disease, n (%) 3 (3.3) 10 (1.0) 13 (1.4) 9 (1.5) 7 (0.7) 9 (0.9) Difficult care situation at home, n (%) 1 (1.1) 8 (0.8) 12 (1.3) 8 (1.3) 14 (1.4) 12 (1.3) Social problems, n (%) – 7 (0.7) 9 (1.0) 11 (1.8) 8 (0.8) 13 (1.4) Weight control, n (%) – 6 (0.6) 8 (0.8) 6 (1.0) 6 (0.6) 7 (0.7) Others, n (%) 5 (5.6) 43 (4.5) 31 (3.3) 21 (3.4) 43 (4.4) 28 (3.0) Any treatment difficulties, n (%) 38 (42.2) 380 (39.8) 387 (41.0) 254 (41.1) 364 (37.1) 351 (37.0) View Large Discussion GPs in our study reported difficulties in treating the HF patients in 1066 of the 3282 patients with HF (32.5%). More severe HF was associated with more treatment difficulties. In addition, five comorbidity groups were associated with a higher risk for GP-reported treatment difficulties: asthma/chronic obstructive pulmonary disease, allergies/drug intolerance, renal insufficiency, atherosclerosis/peripheral arterial occlusive disease and cardiac arrhythmias. Patient-reported psychosocial distress was also significantly associated with treatment difficulties and the effect size for distress was similar to that of the somatic comorbidities. Strengths and limitations In this observational study, the comorbidities of a large cohort of 3282 patients with HF were comprehensively assessed through interviews with the treating GPs. This generated an overview of comorbidities present in patients with HF, independent of biases created through claims data or by pre-selected comorbidities. Comorbidities were grouped by an existing list of 46 chronic conditions (MultiCare list of chronic conditions (19)) established for older primary care patients, which allows potential comparisons of comorbidities with other studies using the MultiCare list. However, some limitations of the present study deserve mentioning: due to its focus on chronic conditions of the (extensive) MultiCare list of chronic conditions, the results of these analyses are limited to the investigated chronic conditions. We cannot exclude that there may be other less common chronic or acute diseases, which may also cause treatment problems. Furthermore, this was an exploratory investigation of the baseline data of the RECODE-HF study. Due to the study procedure (10), the ratio of patients with psychosocial distress in the study population was raised. However, we controlled for the effect of psychosocial distress in the model, so that the association between the comorbidities in the model and treatment difficulties were not affected by the effect of psychosocial distress; also, descriptive data on treatment difficulties stratified by psychosocial distress are provided as supplemental material. During the GP interview, we asked the GP to disclose the patients’ acute and chronic illnesses first. Afterwards, we asked if there were any treatment difficulties. This order may have biased the answers regarding treatment difficulties. The association between comorbidities and treatment difficulties therefore may be overestimated. Furthermore, the comorbidities from the Charlson Index were addressed directly, followed by the question which further comorbidities a patient showed. Hence, we cannot exclude that comorbidities of the Charlson Index were reported more frequently than comorbidities which were reported on the request to name all further acute and chronic illnesses the patient currently had. However, we did not aim to present the prevalence of comorbidities, but to investigate which comorbidities may affect HF treatment. Thus, we assume that the GP named all comorbidities relevant to HF treatment whether a comorbidity was directly addressed in the Charlson Index or not. Lastly, the GP’s response rate in this study was low (6.6%). The high performers among the GPs were probably more likely to take part in the study. These may have been less likely to report treatment problems than low performers. The prevalence of treatment problems may therefore be underestimated. However, the patients of these GPs are likely to represent a broad range of all kinds of patients (and treatment problems) independently of the GPs’ performance. It hence seems unlikely that the factors associated with treatment problems are biased by the low response rates of the GPs. Comorbidities and treatment difficulties Somatic comorbidities The most frequent types of GP treatment difficulties were ‘interaction between HF treatment and comorbid disease/multimorbidity’ followed by ‘non-adherence’. This shows a potential need for targeted treatment recommendations concerning certain comorbidities as well as non-adherence in general practice. Table 4 gives an idea of which comorbidities might be associated with certain types of treatment difficulties. While the proportion of patients with the treatment difficulty ‘interaction between HF treatment and comorbid disease/multimorbidity’ was relatively high for a broader range of comorbidities, non-adherence occurred in a higher proportion of patients with asthma/chronic obstructive pulmonary disease and atherosclerosis/peripheral arterial occlusive disease. So far no studies investigated treatment difficulties in primary care HF patients. One study investigated treatment dilemmas in hospitalized HF patients. Lien et al. found that none of the 116 patients investigated had HF as their only disease and 90% took four or more different medications (8). Even though the comorbidities and treatment problems of both studies are not comparable due to the different settings of the study, this underlines the high frequency of comorbidity and polypharmacy in HF patients. A structure to address comorbidities has been provided in guidelines by Muth et al. in 2014 (20) (see below); but so far, HF treatment guidelines differ greatly regarding the handling of comorbidities. While some incorporate own sections for selected comorbidities (21–23), others just mention effects of comorbid diseases unsystematically within treatment recommendations (24,25). Some HF guidelines already included additional chapters regarding asthma/chronic obstructive pulmonary disease (21–23), cardiac arrhythmias (23,26) and renal insufficiency (21,23,26). Medication intolerance (which is included in the comorbidity group ‘allergies/drug intolerance’ in the present study) is mentioned in the guidelines in combination with pharmacological treatment (21,23–26). ACE-inhibitor intolerance is mentioned particularly often and in detail. Atherosclerosis/peripheral arterial occlusive disease is briefly mentioned in only one guideline (24). In sum, each of the five comorbidity groups has been addressed in one of the guidelines, but no guideline addressed all of them. Psychosocial distress as defined in this study occurred in 30.2% of the HF patients. Scherer et al. reported a similar point—prevalence of 27.5% (80 of 291 patients) HF patients with psychosocial distress (27)— but the selection criteria differed between both studies. We assume that we identified less patients with psychosocial distress in our study than that in Scherer et al.’s study, because we used an algorithm accounting for overlapping symptoms between HF and anxiety/depression, resulting in a more conservative algorithm. Due to our study design, we randomly excluded about 20% of the patients without psychosocial distress. This raised the number of patients with psychosocial distress in our study and might have led to a comparable number of patients with psychosocial distress in both studies. The percentage of GP-reported treatment difficulties in our study was significantly higher in patients with psychosocial distress than in those without in bivariate and multivariable analyses. Anxiety and depression are already addressed by some guidelines (21,23,26,28,29), but so far depression/anxiety treatment has not been proven to improve HF prognosis. However, this analysis showed that psychosocial distress is associated with treatment difficulties in primary care with similar effect size as found for somatic comorbidities. When considering the comorbidity frequencies in each line of Table 4, the numbers indicate no clear link between psychosocial distress and one type of treatment difficulty; psychosocial distress might rather increase the overall risk of treatment difficulties. Therefore, it seems appropriate to address anxiety and depression in HF guidelines. Adherence is a key issue in treating patients with HF, because it is a disease whose treatment includes many recommendations regarding lifestyle and lifelong adherence to medication. Given that in 346 of all 3282 HF patients (10.5%) non-adherence was reported as a treatment difficulty and real non-adherence rates are even likely to be higher, guideline recommendations targeting non-adherence in HF (as implemented in guidelines for coronary heart disease (30) or cardiovascular prevention (31)) would be helpful. Implications for research and practice To support clinical practice, it could be helpful to include instructions on how to handle non-adherence as well as comorbidities in HF clinical guidelines. Muth et al. already recommended considering disease–disease, disease–drug and drug–drug interactions for comorbidities in clinical guidelines (20). This study gives an idea of which comorbidities should be addressed. In a next step, the specific treatment difficulties for each comorbidity should be further assessed in qualitative studies. Then, it will be possible to establish focused recommendations. Furthermore, it seems to be necessary to investigate whether or not GP-rated treatment difficulties lead to worse HF prognoses and if addressing certain comorbidities in HF guidelines might lead to better HF prognoses. Conclusion Five comorbidity groups as well as patient-reported psychosocial distress were significantly associated with a higher risk of GP-reported treatment difficulties. Further efforts to address comorbidities in clinical guidelines could be built on these results. Acknowledgements We thank all GPs and patients for their good collaboration. Members of the RECODE-HF Study Group: Winfried Adam, Cassandra Behrens, Eva Blozik, Sigrid Boczor, Marion Eisele, Malte Harder, Christoph Herrmann-Lingen, Agata Kazek, Dagmar Lühmann, Anja Rakebrandt, Koosje Roeper, Martin Scherer, Stefan Störk, Jens-Martin Träder. Declarations Funding: The study has been funded by the German Federal Ministry of Education and Research (grant numbers 01GY1150 and 01EO1004). Ethical approval: The study was approved by all local ethics committees (Medical Association of Hamburg, Approval No. PV3889; Ethics Committee of the Medical Faculty of the University of Würzburg, Approval No. 125/12, Ethics Committee at the University of Göttingen Medical Center, Approval No. 19/8/11). All study participants gave written informed consent before participating in the study. Conflict of interest: SB received fees for part-time lecturer/statistical consulting of Asklepios Medical School GmbH. EB is employed at Helsana Health Insurances, Zürich, Switzerland. CH-L receives royalties from Hogrefe Huber publishers for the German HADS version. All other authors declare that they have no competing financial interests. Non-financial competing interests: ME and EB are members of the German College of General Practitioners and Family Physicians. 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Family Practice – Oxford University Press
Published: Jan 29, 2018