Tilburg University
Understanding how to improve chronic care
Drewes, H.W.
Publication date:
2012
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Link to publication in Tilburg University Research Portal
Citation for published version (APA):
Drewes, H. W. (2012). Understanding how to improve chronic care: Using variation to gain insight. Gildeprint Drukkerijen.
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Uitnodiging
voor het bijwonen van de openbare verdediging vanmijn proefschrift:
Understanding how to
improve chronic care:
using variation to
gain insight
Op woensdag 21 november om 16.00 uur
in de Aula van Tilburg University, Warandelaan 2, te Tilburg.
Aansluitend bent u van harte welkom
op de receptie.
Hanneke Drewes
Jan Vethstraat 80 6813 HM Arnhem H.Drewes@iq.umcn.nl Paranimfen: Irene Kok I.L.Kok-2@umcutrecht.nl Lidwien Lemmens Lidwien.Lemmens@rivm.nlUnderstanding how to improve chronic care:
using variation to gain insight
Understanding how to improve chronic care:
using variation to gain insight
The research described in this thesis was carried out at the Department of Tranzo, Tilburg University and the Centre for Prevention and Health Services Research, National Institute for Public Health and the Environment (RIVM).
The studies described in this thesis were financed by the National Institute for Public Health and the Environment and the Dutch Health Care Inspectorate (IGZ).
Financial support for the publication of this thesis by the National Institute for Public Health and the Environment and Tilburg University is gratefully acknowledged.
Cover design: Robert Wevers
Lay-out and printing: Gildeprint Drukkerijen, Enschede, the Netherlands ISBN: 978-94-6108-358-6
©H.W. Drewes, 2012
Understanding how to improve chronic care:
using variation to gain insight
Proefschrift
ter verkrijging van de graad van doctor aan Tilburg University
op gezag van de rector magnificus, prof. dr. Ph. Eijlander,
in het openbaar te verdedigen ten overstaan van een door het college voor promoties aangewezen commissie in de aula van de Universiteit
op woensdag 21 november 2012 om 16.15 uur door
Hanneke Wil-Trees Drewes
Promotiecommissie
Promotor: Prof. dr. G.P. Westert Copromotores: Dr. C.A. Baan
Dr. ir. B.R. Meijboom Overige leden: Prof. dr. A.A. de Roo
Contents
Chapter 1 General introduction 7
Part 1: Explaining the variation in effectiveness between chronic care management
evaluations
Chapter 2 The effectiveness of chronic care management for heart failure: 21 meta-regression analyses to explain the heterogeneity in outcomes
Chapter 3 Chronic care management: how to best deal with the variation in its 49 effectiveness?
Part 2: Exploring the association between chronic care management and patient
outcomes in daily care practice
Chapter 4 Differences in patient outcomes and chronic care management of oral 65 anticoagulant therapy: an explorative study
Chapter 5 Measuring chronic care management experiences of patients with 79 diabetes: PACIC and PACIC+ validation
Chapter 6 Exploring the association between patient experiences and outcomes 97 of diabetes care
Part 3: Exploring the variation in implementing chronic care management
Chapter 7 Needs and barriers to improve the cooperation in oral anticoagulant 113 therapy: a qualitative study.
Chapter 8 Chronic care management in a new organizational context: 139 experiences within Dutch care groups
Chapter 10 General discussion 187
Summary 203
Samenvatting (Summary in Dutch) 211
List of abbreviations 219
Dankwoord (Acknowledgements) 223
Curriculum Vitae 229
Chapter 1
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Context
Chronic diseases pose significant challenges to health care systems worldwide1-3. Many
countries have to deal with a tremendous burden of chronic diseases because the mortality and morbidity are higher than that of any other condition. The number of people with chronic diseases is even expected to increase which can partly be attributed to the double ageing of the population1, 4. Besides the fact that countries have to deal with an increased
need of chronic care services, health care systems traditionally fail to meet the needs of people with chronic diseases. In particular, the passive role of the patient combined with the reactive and fragmentised physician care that characterise many health care systems are inappropriate for people with chronic care demands2, 5-7. Meanwhile, countries have to
deal with pervasive quality of care problems. Chronic care is more than once not congruent to the evidence based medicine incorporated in guidelines and protocols8. In addition,
unexplained variation in the delivery of health care services still exists9. Thus, many countries
are questioning which actions are needed to improve chronic care.
Chronic care management
During the past decades, numerous interventions such as disease management and integrated care programs were introduced to redesign chronic care1, 2. These so-called
‘chronic care management’ initiatives all have their own specific characteristics10. For
instance, disease management interventions focus on a single disease, whereas integrated care interventions focus on the total medical condition of the patient. Although differences can be identified between these interventions, they are all multicomponent interventions that strive for quite similar intermediate goals, namely, to improve the cooperation between professionals, foster patient-centeredness, promote evidence-based medicine, and adopt a pro-active approach to improve quality of care. In addition, all initiatives include several chronic care model (CCM) components.
The CCM of Wagner is a widely accepted guide to improve chronic care (Figure 1)11, 12.
The CCM consists of six components that all support chronic care to achieve the best possible chronic care management. Four CCM components should be incorporated at the practice level. The first component is self-management support which aims to help patients live with their condition. For example, this includes the structural incorporation of motivational interviewing in regular consultations and patient-guidelines. The second component, delivery system design, considers the organisation of the care provision, which could become more appropriate for instance by pro-actively scheduling consultations. Third,
decision support, focusses on the integration of evidence-based clinical guidelines into
practice, for instance by the implementation of reminder systems. The fourth component,
clinical information system, aims to capture and use critical information such as feedback on
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which the above-mentioned components are applied and should ideally be facilitated. The health care system/ organisation can support chronic care management by elements such as the introduction of a board that facilitates quality improvement and the incorporation of quality improvement cycles like the plan-do-check action cycle. The last, yet certainly not the least important component, the community, encompasses all elements in the support of chronic care that lie outside the health system, such as governmental payment reforms12, 13.
Because the CCM is the most widely accepted and applied model to improve chronic care, we defined chronic care management as the incorporation of CCM components to the care of patients with chronic diseases. As defined by the World Health Organization (WHO), a chronic disease refers to health problems that require continuous management over a period of years or decades14.
Chapter 1
4 patients with chronic diseases. As defined by the World Health Organization (WHO), a chronic disease refers to health problems that require continuous management over a period of years or decades14.
Figure 1: The Chronic Care Model (CCM)12
Effects of chronic care management elements based on the literature
Particularly in the past decade, many studies and reviews exploring the effectiveness of chronic care management interventions have been published. Mixed results have been reported with regard to the effectiveness of chronic care management interventions for chronic diseases in general1, 11, 15 as
well as for specific chronic diseases, such as chronic obstructive pulmonary diseases (COPD)16, 17,
depression18, 19, diabetes20, 21, and heart failure22, 23.
The variation of effectiveness between chronic care management interventions spans a range of various outcome and process measures. For instance, a review of chronic care management interventions showed inconclusive results on quality of life for patients with asthma, depression, diabetes, and heart failure. Most studies reported no significant improvement or slight deterioration in the quality of life, yet there were also studies that reported significant positive and negative effects15. Similar variation in results on process and outcome measures was identified in
disease-specific reviews. For example, mixed results were observed in a study of chronic heart failure interventions based on outcome measures such as hospitalisation and mortality23.
It is important to understand how this variation arose to enable application of the most appropriate chronic care management intervention. Previous reviews also tried to explain the variation in effectiveness of chronic care management interventions by subgroup analyses21, 23-25.
Although subgroup analyses were frequently applied to identify crucial elements of chronic care management interventions, meta-regression analysis should be used instead26. Meta-regression
analyses, however, are only rarely performed18, 27. For instance, it remains unknown to what extent
Figure 1: The Chronic Care Model (CCM)12
Effects of chronic care management elements based on the literature
Particularly in the past decade, many studies and reviews exploring the effectiveness of chronic care management interventions have been published. Mixed results have been reported with regard to the effectiveness of chronic care management interventions for chronic diseases in general1, 11, 15 as well as for specific chronic diseases, such as chronicR1 R2 R3 R4 R5 R6 R7 R8 R9 R10 R11 R12 R13 R14 R15 R16 R17 R18 R19 R20 R21 R22 R23 R24 R25 R26 R27 R28 R29 R30 R31 R32 R33 R34 R35 R36 R37 R38 R39 11 General introduction
The variation of effectiveness between chronic care management interventions spans a range of various outcome and process measures. For instance, a review of chronic care management interventions showed inconclusive results on quality of life for patients with asthma, depression, diabetes, and heart failure. Most studies reported no significant improvement or slight deterioration in the quality of life, yet there were also studies that reported significant positive and negative effects15. Similar variation in results on process
and outcome measures was identified in disease-specific reviews. For example, mixed results were observed in a study of chronic heart failure interventions based on outcome measures such as hospitalisation and mortality23.
It is important to understand how this variation arose to enable application of the most appropriate chronic care management intervention. Previous reviews also tried to explain the variation in effectiveness of chronic care management interventions by subgroup analyses21, 23-25. Although subgroup analyses were frequently applied to identify crucial elements of
chronic care management interventions, meta-regression analysis should be used instead26.
Meta-regression analyses, however, are only rarely performed18, 27. For instance, it remains
unknown to what extent the comprehensiveness of chronic care management interventions is associated with the effectiveness of chronic care (e.g., clinical outcomes). True insight in the variation in effectiveness between chronic care management interventions is still lacking.
Effects of chronic care management elements in daily care practice
Even though heterogeneity in outcomes between chronic care management evaluations existed, the overall effectiveness on the quality of care is expected to be positive in most countries. Positive results were also found in the Netherlands. For COPD, the bottom-up implementation of disease management programs led to statistically significant improvement in various quality of life dimensions, dyspnoea, and patient experiences28. For
patients with diabetes, an association was shown between disease management programs and several outcome measures, such as health-related quality of life and compliance with self-care behaviour29.
Hence, many health care professionals, managers, and policy makers introduce or facilitate chronic care management components. The available evidence regarding chronic care management, however, is still limited. In addition to the unexplained variations in outcomes, which has limited the insight into the successful elements of chronic care, the field is also hampered by previous studies that were mostly based on intervention studies performed by highly motivated practices with pre-dominantly pre-post analysis11.
Furthermore, most studies ignored the multilevel structure in evaluations30. In addition to
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such as the GP practice. However, it is unknown to what extent the effectiveness of chronic care management is associated with the second level.
Given the limitations of previous research, it is of great interest to further scrutinise the currently inconclusive results by studying the association of chronic care management with structure, process, and outcome variables in daily chronic care practice.
Implementing chronic care management
Variation in chronic care managements’ effectiveness can besides intervention and evaluation characteristics also be explained by its implementation process31-33. Incorporating chronic
care management requires modifying medical practices and thus behavioural changes of professionals and patients. This requirement implies that many alternative factors, in addition to those directly related to the professionals and the patients, influence the overall effectiveness11, 34, 35. One of the major counterproductive determinants for the sustainability
of chronic care management interventions was the workload of health care professionals and financial constraints by fragmentised payment systems36.
Hence, many countries have already introduced new payment systems, yielding new organisations such as accountable care organisations (ACOs) in the US, clinical commissioning groups (CCGs) in the UK, and care groups in the Netherlands, to facilitate chronic care management37. In 2007, the Dutch government implemented a new payment system, the
bundled payment system, which created care groups to take account for providing chronic care for specific diseases38, 39. Care groups operate as a contracting entity to cover a full
range of chronic care services for one or more chronic diseases (i.e., disease management programs) for a fixed time period. The care group is responsible for all assigned patients in the care program and either delivers services itself or subcontracts other care providers38.
In 2010, 97 care groups - including more than 75 percent of the Dutch GPs - offered disease management programs for diabetes paid by bundled payment37.
Because countries have introduced new organisations to improve chronic care management, it is of interest to explore the barriers to chronic care management within a specific context11, 34, 35, 40. However, the barriers of chronic care management within
specific contexts are not yet structurally identified11. To use the full potential of chronic care
management, it is of utmost importance to identify the barriers, which will then provide a starting point for further improvement of chronic care management31.
Research objectives
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1. To explain the variation in effectiveness between chronic care management evaluations. 2. To explore the association between chronic care management and the patient outcomes
in daily care practice.
3. To explore the variation in implementing chronic care management addressing the experiences, needs, and barriers for chronic care management in daily care practice. To understand how chronic care can be improved while strengthening the link with daily care practice, two case studies were used, namely, oral anticoagulant therapy and diabetes care. Additional insight into chronic care management specific to oral anticoagulant therapy is of interest given the long experience with chronic care management as well as the need for improvement41-44. Oral anticoagulant therapy is provided by oral anticoagulant clinics
(ACs). ACs provide chronic care according to CCM principles: pro-actively control patients using oral anticoagulants, support evidence-based medicine by IT and (multidisciplinary) guidelines, stimulate self-management of patients, and coordinate with other professionals about patient care needs. Notwithstanding the fact that the Dutch oral anticoagulant therapy is qualitatively high, substantial variation in patient outcome exists between regions45. Moreover, oral anticoagulants are among the drugs associated with the highest
levels of avoidable hospitalisations.
In contrast to oral anticoagulant therapy, chronic care management elements for diabetes were introduced only in the past decade7. Diabetes care in the Netherlands, as well
as in other countries, is the fastest reformed field of chronic care, and it is the frontrunner in which chronic care management elements are incorporated2, 7. Coincidentally, it was the
first field for which a new payment reform, the bundled payment system, was applied38.
Insight into the daily care practice and needs within this new organisational context is of value to achieve the maximum effect of chronic care management.
Thesis outline
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Part 1: Explaining the variation in effectiveness between chronic care management evaluations
Chapter 2 presents the results of a systematic review of the literature on the effectiveness
of chronic care management for patients with heart failure. Meta-regression analysis was applied to explain the heterogeneity in outcomes between the studies.
In chapter 3, a comprehensive overview is given of chronic care management evaluations and their variations for four major chronic diseases: COPD, depression, diabetes, and heart failure. The first steps to address the unexplained variation of chronic care management’s effectiveness are given.
Part 2: Exploring the association between chronic care management and patient outcomes in daily care practice
Chapter 4 explores whether variation in patient outcomes regarding oral anticoagulant
therapy is associated with chronic care management. The results of the questionnaires completed by all Dutch anticoagulant clinics that provide extramural thrombosis care were combined with patient outcomes of those anticoagulant clinics.
Chapter 5 contains the results of the validation study of the Patient Assessment of
Chronic Illness Care (PACIC) to gain insight into its usefulness to measure the chronic care management experience of patients. The PACIC could possibly be improved by additionally including one of the pillars of chronic care management, namely, cooperation. In addition, this chapter presents results about the extent to which variation on PACIC outcomes is related to the GP-practice level.
Subsequently, chapter 6 presents the results of the study in which the association between patients’ chronic care management experiences and patient outcomes was explored. The PACIC+ was used to measure patients’ chronic care management experiences. Data from the completed questionnaires of more than 1700 patients were coupled with GP data registries. Part 3: Exploring the variation in implementing chronic care management
Chapter 7 includes an exploration of professionals experiences, needs, and barriers to
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In chapter 8, results of a mixed-methods sequential explanatory design are presented. The extent of chronic care management was quantitatively assessed with the Assessment of Chronic Illness Care (ACIC) and subsequently used in semi-structured interviews to explore professionals’ preferences and barriers to improve chronic care management.
Chapter 9 provides a more detailed analysis of the study in Chapter 8, with an emphasis on
the results pertaining to self-management support. Self-management support is assumed to be one of the crucial components of effective chronic care management, yet insight in daily care practice experiences of professionals regarding self-management support, their experienced needs, and barriers to improve self-management support is limited.
Chapter 10 summarises the main findings of each of the three parts of this PhD study.
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18. Bower P., Gilbody S., Richards D., Fletcher J., Sutton A. (2006) Collaborative care for depression in primary care. Making sense of a complex intervention: systematic review and meta-regression.
Br J Psychiatry, 189, 484-93.
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20. Norris S. L., Chowdhury F. M., Van Le K., Horsley T., Brownstein J. N., Zhang X., Jack L., Jr., Satterfield D. W. (2006) Effectiveness of community health workers in the care of persons with diabetes. Diabet Med, 23(5), 544-56.
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on hospital length-of-stay and readmission. Nurs Res, 54(4), 255-64.
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24. Shojania K. G., Ranji S. R., McDonald K. M., Grimshaw J. M., Sundaram V., Rushakoff R. J., Owens D. K. (2006) Effects of quality improvement strategies for type 2 diabetes on glycemic control: a meta-regression analysis. Jama, 296(4), 427-40.
25. Taylor S. J., Candy B., Bryar R. M., Ramsay J., Vrijhoef H. J., Esmond G., Wedzicha J. A., Griffiths C. J. (2005) Effectiveness of innovations in nurse led chronic disease management for patients with chronic obstructive pulmonary disease: systematic review of evidence. Bmj, 331(7515), 485. 26. Clark A. M., Savard L. A., Thompson D. R. (2009) What is the strength of evidence for heart
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30. Sidorenkov G., Haaijer-Ruskamp F. M., de Zeeuw D., Bilo H., Denig P. (2011) Review: relation between quality-of-care indicators for diabetes and patient outcomes: a systematic literature review. Med Care Res Rev, 68(3), 263-89.
31. Berwick D. M. (2008) The science of improvement. Jama, 299(10), 1182-4.
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33. Grol R. P., Bosch M. C., Hulscher M. E., Eccles M. P., Wensing M. (2007) Planning and studying improvement in patient care: the use of theoretical perspectives. Milbank Q, 85(1), 93-138. 34. Cabana M. D., Rand C. S., Powe N. R., Wu A. W., Wilson M. H., Abboud P. A., Rubin H. R. (1999)
Why don’t physicians follow clinical practice guidelines? A framework for improvement. Jama, 282(15), 1458-65.
35. Grol R., Grimshaw J. (2003) From best evidence to best practice: effective implementation of change in patients’ care. Lancet, 362(9391), 1225-30.
36. Steuten L. M., Vrijhoef H. J., Spreeuwenberg C., Van Merode G. G. (2002) Participation of general practitioners in disease management: experiences from The Netherlands. Int J Integr Care, 2, e24.
37. de Bakker D. H., Struijs J. N., Baan C. B., Raams J., de Wildt J. E., Vrijhoef H. J., Schut F. T. (2012) Early results from adoption of bundled payment for diabetes care in the Netherlands show improvement in care coordination. Health Aff (Millwood), 31(2), 426-33.
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diabetes care in the Netherlands: The first tangible effects Bilthoven: National Institute for Public
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42. Howard R. L., Avery A. J., Slavenburg S., Royal S., Pipe G., Lucassen P., Pirmohamed M. (2007) Which drugs cause preventable admissions to hospital? A systematic review. Br J Clin Pharmacol, 63(2), 136-47.
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PART I
Chapter 2
The effectiveness of chronic care management for
heart failure: meta-regression analyses to explain
the heterogeneity in outcomes
H.W. Drewes, L.M.G. Steuten, L.C. Lemmens, C.A. Baan, H.C. Boshuizen, A.M.J. Elissen, K.M.M. Lemmens, J.A.C. Meeuwissen, H. J.M. Vrijhoef
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Abstract
Background: Heart failure poses significant challenges to health care systems. To support
decision making on how to best redesign chronic care by studying the heterogeneity in effectiveness across chronic care management evaluations for heart failure.
Methods: A systematic review including meta-regression analyses to investigate three
potential sources of heterogeneity in effectiveness: study quality, length of follow-up, and number of chronic care model (CCM) components.
Results: Our meta-analysis showed that chronic care management reduces mortality by
a mean of 18% (95% CI: 0.72-0.94) and hospitalisation by a mean of 18% (95% CI: 0.76-0.93) and improves quality of life by 7.14 points (95% CI: -9.55 - -4.72) on the Minnesota Living with Heart Failure questionnaire. We could not explain the considerable differences in hospitalisation and quality of life across the studies.
Conclusion: Chronic care management significantly reduces mortality. Positive effects on
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The effectiveness of chronic care management for heart failure
Introduction
Heart failure poses significant challenges to health care systems. Health care demands as well as health care costs are likely to rise1, 2, since the prevalence of heart failure is expected
to increase substantially due to ageing and increased survival3-5. Moreover, there is a
considerable gap between appropriate care for chronic conditions and the care actually received. Finally, there is an increasing need for more patient centred care6-8.
To address these challenge9, 10, various approaches have been proposed to improve
the care for patients with heart failure. Perhaps best known are the concept of disease management and the chronic care model (CCM), while case management, integrated care, and care coordination are also often mentioned in relation to chronic care management11.
The CCM is widely adopted as an evidence-based tool to improve chronic care12, 13, 14.
Notwithstanding the awareness among policy makers, health care professionals, and patients of the importance of chronic care management, coming to strong conclusions regarding the effectiveness of chronic care management interventions has been limited. Substantial heterogeneity between study outcomes - the variation in effectiveness between studies is higher than is to be expected by chance alone - limits insight into the effectiveness of chronic care management13, 15, 16. This statistical heterogeneity is not only caused by
clinical diversity (e.g., differences in interventions, like type and number of included CCM components, and outcomes studied), but also by methodological diversity (e.g., differences in length of follow-up and study design).
Insight into heterogeneity in effectiveness is needed to support the understanding of and decision making on chronic care management strategies. Some reviews tried to address the heterogeneity in outcomes by subgroup analysis17-20. However, meta-regression analyses
are needed to determine whether the differences between subgroups are stronger than is to be expected by chance alone. Although meta-regression analysis is a more promising tool to identify the characteristics of programs that predict better outcomes15, this has only been
performed once restricted to randomized clinical trials21.
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Methods
Literature searchElectronic database searches for English language systematic reviews and meta-analyses published between 1995 and 2009 were conducted in Medline and CINAHL, using the following Medical Subject Headings (MeSH): patient care team, patient care planning, primary nursing care, case management, critical pathways, primary health care, continuity of patient care, guidelines, practice guideline, disease management, comprehensive health care, and ambulatory care. These were combined with the MeSH term heart failure. In addition, disease state management, disease management, integrated care, coordinated care, and shared care in combination with heart failure were searched as text words in title and/or abstract words.
Study inclusion and data extraction
Systematic reviews and primary papers were included if they focused on: 1) heart failure as the main condition of interest; 2) adult patients as the main receivers of the interventions; and, 3) interventions addressing at least two CCM components14. Studies published before
1995 were excluded; around that year chronic care management strategies became an important issue22. Case reports and expert opinions were also excluded. Two reviewers
(H.D. and L.S.) independently extracted data, using separate data entry forms for systematic reviews and primary papers. Disagreements were resolved by consensus with the third author (L.L).
Assessing the sources of heterogeneity
Substantial heterogeneity in effectiveness across chronic care management interventions is likely, that is, differences in study outcomes are probably greater than is to be expected by chance alone13, 15. We identified three factors which may explain the heterogeneity in
effectiveness: study quality, length of follow-up, and the number of CCM components. First, study quality is expected to explain part of the heterogeneity in outcomes, but this has not yet been tested by means of meta-regression analyses17-20. We used the
validated Health Technology Assessment - Disease Management (HTA-DM) instrument to classify the primary studies as demonstrating either low (<50 points), moderate (50 to 69 points), or high quality (70 to 100 points)23. The HTA-DM instrument reliably measures the
methodological quality of health technology assessments of disease management23. We
used this instrument to determine to what extent study quality explains the heterogeneity in results between studies.
Second, length of follow-up was assessed as chronic care management interventions require behavioural, organisational and cultural changes which tend to take considerable time to take effect24. Length of follow-up equals the reported number of months of the
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The effectiveness of chronic care management for heart failure
Third, the number of CCM components was taken into account, because more comprehensive programs were expected to be more effective25. The number of CCM
components addressed by the chronic care management interventions was identified following the coding scheme of Zwar et al.: self-management support (SMS) (i.e., supporting patients to manage their condition for instance by routinely assessing progress and education); delivery system design (DSD) (i.e., the organisation of providing care such as planned visits and other roles/teams); decision support (DS) (i.e., integration of evidence based clinical guidelines into practice for instance by reminder and feedback systems); and, clinical information systems (CIS) (i.e., information systems to capture and use critical information like reminders and feedback on performance)26.
Data analyses
Data collected from reviews were descriptively analysed and data gathered from primary studies were descriptively analysed and meta-analysed. The outcomes measured most frequently, i.e., hospitalisation rate, mortality and quality of life, were meta-analysed. Review Manager (RevMan 5.0.2) was used to compute the pooled overall effects and the pooled effects for the subgroups of the three factors i.e., quality of study (poor, moderate, or good), length of follow-up (less than one year or longer), and number of components (two, three, or four). Pooled risk ratios for dichotomous outcomes were analysed with the Mantel-Haenszel method using the random effect model27. Pooled mean differences for
continuous outcomes were analysed with the random model of Dersimonian and Laird27.
Meta-regression analysis was performed to determine to what extent the heterogeneity is explained by the quality of the studies, the length of follow-up, and the number of CCM components, if at least ten studies could be included in the analyses28. In contrast with the
subgroup analyses, all factors were taken into account as continuous variables. The effect sizes of primary studies were weighted using the inverse variance weight formulas27 and
imported together with the covariates into the SAS statistical package (version 9.2)29. The
extent to which the three factors explained the variance between studies was examined by fitting of univariable meta-regression models30. The relative decrease of the between-study
variance in the univariable model compared to an intercept only model was interpreted as the percentage of heterogeneity explained.
Results
Results of the search
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Figure 1: Study in/exclusion flowchart
Reviews excluded: n=126
Reasons (reviews may be excluded for more than one reason): 1) Focus on single-component interventions: n=108 2) No systematic review or meta-analysis: n=103 3) Main focus on other condition than HF: n=46 4) Main focus on other than adult population: n=41
Potentially relevant reviews identified and title/abstract screened for retrieval: n=147
Reviews retrieved for full text evaluation: n=21
Primary papers retrieved for full text evaluation: n=54 Primary papers excluded: n=7
Reasons:
1) Single component intervention: n=5
2) No relevant effectiveness measure reported: n=1 3) Full text not in English: n=1
Primary studies included in the analysis: n=46 Reviews excluded: n=6
Reasons:
1) No systematic review or meta-analysis: n=3 2) Focus on single-component interventions: n=2 3) No relevant effectiveness measure reported: n=1
Systematic reviews included in the analysis: n=15 Primary papers identified from included reviews and title/abstract screened for retrieval: n=107
Primary papers excluded: n=53
Reasons (primary papers may be excluded for more than one reason): 1) Single-component intervention: n=12
2) Main focus on other condition than HF: n=6 3) No full text available: n=34
4) Publication before 1995: n=9 5) Other: n=2
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The effectiveness of chronic care management for heart failure
Findings from the systematic reviews
The definitions of chronic care management as well as the nature of the included interventions varied. Some interventions were purely physician driven, other were nurse-led; some were clinic-based, other involved home care, etc. (Appendix 1). A common aspect of the included interventions was a strong focus on reducing hospital admissions, and hence on (post)discharge planning and self-management. The reported outcome measures varied. Almost all reviews reported hospitalisation, whereas other outcomes, like patient satisfaction and quality of life, were measured by less than half of the reviews.
Overall, the reviews showed positive effects, although with substantial heterogeneity between study outcomes. Most meta-analyses revealed a significant reduction on all-cause hospitalisation17, 19-21, 31-33 with a relative risk reduction ranging from 12 to 25 per cent. Results
on mortality were less convincing; only two reviews reported a significant positive effect19, 21. Results on quality of life were inconclusive, as it was less frequently used as an outcome
measure and only once meta-analysed (Appendix 1).
Several meta-analyses included subgroup analyses to determine whether specific variables, such as age or length of follow-up, were associated with the effectiveness of chronic care management interventions. To find out whether the differences between subgroups were stronger than was to be expected by chance alone, a meta-regression analysis should be performed. However, we found only one study that included a meta-regression analysis21. Since Gohler et al. limited this meta-regression analysis to RCT’s,
insight into the effect of the three selected factors, i.e., study quality, length of follow-up and number of components, is limited.
Findings from the primary studies
Of the 46 included primary studies, 44% scored ‘good’ on methodological quality34-53, 41%
scored ‘moderate’54-73, and 15% scored ‘poor’74-80. Length of follow-up varied between
three to 50 months; two studies reported more than one year46, 50. The numbers of studies
addressing four, three, or two CCM components were eighteen, seventeen and eleven studies, respectively. The component of chronic care management included most frequently was SMS (n=43), followed by DSD (n=38), CIS (n=37), and DS (n=27) (Table 1).
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(e.g., by providing education, self-management monitoring tools, exercise or diet advice), usually with a strong focus on reducing hospitalisation.
Hospitalisation
The measures of all-cause and HF hospital admission varied between the studies (e.g., at least one hospitalisation, length of stay, cumulative hospital days). The relative risk of at least one hospitalisation for any cause was measured most frequently (n=27)35-37, 39-44, 46-53, 56, 59, 61, 63-66, 69, 71, 80. The result of five studies were not included in the meta-analysis because
of missing data48, 53, 71 or because preliminary results were reported (we only included the
last results of the same primary study)51, 52. In total, 22 studies were included in our
meta-analysis on all-cause hospitalisation (i.e., the number of patients with at least one all-cause hospitalisation during the study period).
The pooled relative risk for all-cause hospitalisation with chronic care management compared to the control intervention (mostly usual care) is 0.82 (95%-CI: 0.72-0.94; I2:84%).
Subgroup analyses showed that studies of good methodological quality, with a follow-up period of at least one year, and studies reporting on interventions including three CCM components demonstrated a significant reduction in the number of patients with at least one all-cause hospitalisation. The associations suggested by the subgroup analyses, like the positive association between the study quality and hospitalisation, were tested by the meta-regression analysis. Meta-meta-regressions showed no significance of the three factors (p>0.50), which implies that these could not significantly explain the heterogeneity between the studies.
Mortality
Twenty-nine studies reporting on all-cause mortality were included in our meta-analysis34-46, 48, 50, 56, 60-66, 74, 75, 77. Overall, the pooled effect showed a significantly reduced relative risk of
mortality (RR: 0.82; 95%-CI: 0.76-0.93; I2=0%). This result implies that the chance to die during
the follow-up period is reduced by 18% for patients receiving chronic care management. Subgroup analyses showed that pooled effects for studies of a moderate quality, with a follow-up period of less than one year, or on three CCM components were not associated with a significant reduction of mortality (Table 2). Meta-regression analysis was used to determine whether the variables were associated with the effect, as no heterogeneity had to be explained (I2=0%). The meta-regression analysis showed that none of the variables was
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The effectiveness of chronic care management for heart failure
Table 1: Ov er vie w of primar y s tudies Author , y ear of public ation Popula tion† In ter ven tion Componen ts†† Follo w -up (mon ths) Quality (s tudy design) ††† Ak osah e t al. (2002) N: 38/ 63; Ag e: 68/76*; Male: 71/43*; NYHA: NR; Coun tr y: U SA Short -t erm, multidisciplinar y, ag gr essiv e-in ter ven tion in HF clinic f ollo wing hospit al dischar ge primarily f ocused on pa tien t educ
ation and medic
ation titr ation. DSD , SMS 12 40 (Other) Ansari e t al. (2003) N: 54/ 51; Ag e: 69/70; Male: 94/98; NYHA: NR; Coun tr y: US A Nur se pr actitioner s initia te and titr at e be ta-block er s super vised b y 2 c ar diologis ts a t a single ac ademic ally a ffilia ted V et er ans Aff air s medic al cen tr e. DSD , DS 12 80 (R CT) Atienz a e t al., (2004) N: 164/ 174; Ag e: 69/67; Male: T ot al: 60; NYHA: 2.5/2.5; Coun tr y: Spain Compr ehensiv e hospit al dischar ge planning , a visit b y the primar y car e ph ysician a ft er dischar ge t o monit or and r ein for ce the educ ational kno wledg e, t elemonit
oring and close f
ollo w -up a t a HF-clinic. DSD , SMS, CIS 12 80 (R CT) Aus tin e t al., (2005) N: 100/ 100; Ag e: 71.9/ 71.8;
Male: 67/64; NYHA: 2.4/2.5; Coun
tr y: UK Car diac r ehabilit ation pr ogr am including pa tien t educ ation, ex er cise tr
aining and lif
es tyle modific ations, and 8-w eekly clinic att endance with c ar diologis t and nur se. DSD , SMS, DS 5.5 70 (R CT) Az ev edo e t al., (2002) N: 157/ 182; Ag e: 69/65; Male: 52.2; NYHA: NR; Coun tr y: Portug al Outpa tien t manag emen t a t HF clinic b y a multidisciplinar y t eam aft er hospit al dischar ge based on curr en t R CT ’s and t ailor ed t o individual’ s pa tien t char act eris tics. DSD , DS 12 40 (CC T) Bena tar e t al., (2003) N: 108/ 108; Ag e: 62/ 63; Male: 36/38; NYHA: T ot al:3.1; Coun tr y: US A Nur se t elemanag emen t model pr
ovided during a period of 3
mon ths a ft er hospit al dischar ge, inc orpor ating an adv anced pr actice nur se super vised b y a c ar diologis
t and home monit
oring de vices t o measur e and tr ans fer ph ysiologic al signs. DSD , SMS, CIS 12 65 (R CT) Blue e t al., (2001) N: 84/ 81; Ag e: 76/ 74; Male: 64/51; NYHA: 3.2/3.18; Coun tr y: Sc otland Nur se specialis
t making a number of planned home visits of
decr easing fr equency , supplemen ted b y t elephone c on tact as needed, t o educ at e, monit or , t each self -monit oring and manag emen
t, liaise with other health c
ar e and social w ork er s, and pr ovide p sy chologic al support. DSD , SMS, DS, CIS 12 75 (R CT) Bouv y e t al., (2003) N: 74/ 78; Ag e: 69/70; Male: 72/60; NYHA: 2.54/2.31; Coun tr y: The Ne therlands Mon thly c onsult ations pr ovided b y tr ained pharmacis t, including an initial in ter vie w r eg ar ding pa tien
ts’ drug use and sub
R1 R2 R3 R4 R5 R6 R7 R8 R9 R10 R11 R12 R13 R14 R15 R16 R17 R18 R19 R20 R21 R22 R23 R24 R25 R26 R27 R28 R29 R30 R31 R32 R33 R34 R35 R36 R37 R38 R39 30 Chapter 2 Table 1: Con tinued Author , y ear of public ation Popula tion† In ter ven tion Componen ts†† Follo w -up (mon ths) Quality (s tudy design) ††† Br anch, (1999) N: 23/ 23; Ag e: T ot al: 66; Male: Tot
al:52; NYHA: NR; Coun
tr y: U SA CHF clinic tha t aims t o ma ximiz e outpa tien t manag emen t b y emplo ying a multidisciplinar y t eam of c ar e pr ovider s and in tensiv e pa tien t and f amily educ ation, c ommunic ation and in volv emen t. DSD , SMS, DS 3 20 (B A) Bull e t al., (2000) N: 40/ 71; Ag e: T ot al: 74; Male: Not s ta
ted; NYHA: NR; Coun
tr y: U SA A pr of essional-pa tien t partner
ship model of dischar
ge planning , including pr ovider educ ation, pa tien t needs assessmen t and in forma tion f or pa tien t and c ar er s giv en b y the nur
ses and social
w ork er s a t the hospit al. SMS, CIS 2 50 (CC T) Capomolla e t al., (2002) N: 112/ 122; Ag e: 56/56; Male:
84/84; NYHA: I-II (%): 66/65; Coun
tr y: It aly Da y hospit al f ollo w -up c ar
e within a HF Unit, which implemen
ted an individualiz ed HF manag emen t pr ogr am b y a multidisciplinar y
team, including educ
ation, DSD , SMS, DS, CIS 12 70 (R CT) Cline e t al., (1998) N: 80/ 110; Ag e: T ot al: 76; Male: T ot al:53; NYHA: 2.6/2.6; Coun tr y: S w eden Educ
ation on HF and self
-manag emen t, with f ollo w -up a t an eas y access nur se dir ect ed outpa tien t clinic f or 1 y ear a ft er dischar ge. The nur ses r eceiv ed a lectur e and c ould c onsults the c ar diologis t. DSD , SMS, DS 12 60 (R CT) Cos tan tini e t al., (2001) N: 283/ 173; Ag e: 72/69; Male: 43/41; NYHA: NR; Coun tr y: US A A c ar diologis t and nur se c ar e manag er a t an ac ademic medic al cen tr e r evie w ed pa tien t’s da
ta and made
guideline-based r ec ommenda tions r eg ar ding A CE inhibit or; E CG and implemen ta tion of daily w eigh ts used f or the c ar e manag er shee t. The nur se pr ovided pa tien t educ
ation, assessed dischar
ge needs, and e valua ted pa tien t’s ability t o c omply with pr escribed plan. DSD , SMS, DS, CIS NR 50 (CC T) DeBusk e t al., (2004) N: 228/ 234; Ag e: T ot al: 72
; Male: 48/54; NYHA: NR; Coun
tr y: US A Nur se c ase manag emen t pr ovided educ ation, s tructur ed telephone sur veillance and tr ea tmen t f or heart f ailur e giv en b y 5 HMO ’s hospit als. Coor dina tion of pa tien ts’ c ar e with primar y c ar e ph ysicians acc or ding the s tudy pr ot oc ol. DSD , SMS, DS, CIS 12 80 (R CT) Dough ty e t al., (2002) N: 100/ 97; Ag e: 73/ 74; Male: 64/57; NYHA: 3.8/3.8; Coun tr y: Ne w Z ealand In tegr at ed primar y/ sec ondar y c ar e in volving a clinic al r evie w at a hospit
al-based HF clinic early a
ft er dischar ge, educ ation sessions, a per sonal diar y t o r ec or d medic
ation and body w
eigh t, in forma tion bookle ts and r egular (12 mon th) clinic al f ollo w -up alt erna ting be tw
een GP and HF-clinic.
DSD
, SMS, DS, CIS
12
80 (R
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The effectiveness of chronic care management for heart failure
Table 1: Con tinued Author , y ear of public ation Popula tion† In ter ven tion Componen ts†† Follo w -up (mon ths) Quality (s tudy design) ††† Br anch, (1999) N: 23/ 23; Ag e: T ot al: 66; Male: Tot
al:52; NYHA: NR; Coun
tr y: U SA CHF clinic tha t aims t o ma ximiz e outpa tien t manag emen t b y emplo ying a multidisciplinar y t eam of c ar e pr ovider s and in tensiv e pa tien t and f amily educ ation, c ommunic ation and in volv emen t. DSD , SMS, DS 3 20 (B A) Bull e t al., (2000) N: 40/ 71; Ag e: T ot al: 74; Male: Not s ta
ted; NYHA: NR; Coun
tr y: U SA A pr of essional-pa tien t partner
ship model of dischar
ge planning , including pr ovider educ ation, pa tien t needs assessmen t and in forma tion f or pa tien t and c ar er s giv en b y the nur
ses and social
w ork er s a t the hospit al. SMS, CIS 2 50 (CC T) Capomolla e t al., (2002) N: 112/ 122; Ag e: 56/56; Male:
84/84; NYHA: I-II (%): 66/65; Coun
tr y: It aly Da y hospit al f ollo w -up c ar
e within a HF Unit, which implemen
ted an individualiz ed HF manag emen t pr ogr am b y a multidisciplinar y
team, including educ
ation, DSD , SMS, DS, CIS 12 70 (R CT) Cline e t al., (1998) N: 80/ 110; Ag e: T ot al: 76; Male: T ot al:53; NYHA: 2.6/2.6; Coun tr y: S w eden Educ
ation on HF and self
-manag emen t, with f ollo w -up a t an eas y access nur se dir ect ed outpa tien t clinic f or 1 y ear a ft er dischar ge. The nur ses r eceiv ed a lectur e and c ould c onsults the c ar diologis t. DSD , SMS, DS 12 60 (R CT) Cos tan tini e t al., (2001) N: 283/ 173; Ag e: 72/69; Male: 43/41; NYHA: NR; Coun tr y: US A A c ar diologis t and nur se c ar e manag er a t an ac ademic medic al cen tr e r evie w ed pa tien t’s da
ta and made
guideline-based r ec ommenda tions r eg ar ding A CE inhibit or; E CG and implemen ta tion of daily w eigh ts used f or the c ar e manag er shee t. The nur se pr ovided pa tien t educ
ation, assessed dischar
ge needs, and e valua ted pa tien t’s ability t o c omply with pr escribed plan. DSD , SMS, DS, CIS NR 50 (CC T) DeBusk e t al., (2004) N: 228/ 234; Ag e: T ot al: 72
; Male: 48/54; NYHA: NR; Coun
tr y: US A Nur se c ase manag emen t pr ovided educ ation, s tructur ed telephone sur veillance and tr ea tmen t f or heart f ailur e giv en b y 5 HMO ’s hospit als. Coor dina tion of pa tien ts’ c ar e with primar y c ar e ph ysicians acc or ding the s tudy pr ot oc ol. DSD , SMS, DS, CIS 12 80 (R CT) Dough ty e t al., (2002) N: 100/ 97; Ag e: 73/ 74; Male: 64/57; NYHA: 3.8/3.8; Coun tr y: Ne w Z ealand In tegr at ed primar y/ sec ondar y c ar e in volving a clinic al r evie w at a hospit
al-based HF clinic early a
ft er dischar ge, educ ation sessions, a per sonal diar y t o r ec or d medic
ation and body w
eigh t, in forma tion bookle ts and r egular (12 mon th) clinic al f ollo w -up alt erna ting be tw
een GP and HF-clinic.
DSD , SMS, DS, CIS 12 80 (R CT) Ducharme e t al., (2005) N: 115/ 115; Ag e: 68/70; Male: 73/71; NYHA: 3.3/3.2; Coun tr y: Canada A s tructur ed multidisciplinar y outpa tien t clinic en vir onmen t with comple te access t o c ar diologis
ts and allied health pr
of essionals, pa tien t educ ation and t elephone f ollo w -up. DSD , SMS, CIS 6 80 (R CT) Dunag an e t al., (2005) N: 76/ 75; Ag e: 71/ 69; Male: 41/47; NYHA: 2.9/2.9; Coun tr y: U SA Scheduled t elephone c alls b y specially tr ained nur ses w orking a t the hospit al pr omoting self -manag emen t and guideline-based ther ap y as pr escribed b y primar y ph ysicians, additional t o an educ ational bookle t tha
t is part of usual primar
y c ar e. SMS, DS, CIS 12 80 (R CT) Ekman e t al., (1998) N: 79/ 79; Ag e: T ot al: 80; Male: 58/63; NYHA: 3.2/3.2; Coun tr y: Sw eden A nur se monit or ed, outpa tien t c ar e pr ogr am aiming a t s ymp tom manag emen t, including educ ation, c ooper ation of nur ses and doct or s, t elephone f ollo w -up s ta ted in pr actic al guidelines. DSD , SMS, DS, CIS 6 70 (R CT) Fonar ow e t al., (1997) N: 214/ 214; Ag e: T ot al: 52; Male: T ot al: 81; NYHA: NR; Coun tr y: US A Compr ehensiv e HF manag emen t pr ogr
am, including guideline
based medic
ation manag
emen
t, nur
se pr
ovided individual and
gr oup educ ation and c ar diologis t f ollo w -up c ar e and t elephone follo w -up a ft er dischar ge. SMS, DS, CIS 6 50 (B A) Ga ttis e t al., (1999) N: 90/ 91; Ag e: 72/63*; Male: 69/67; NYHA: NR; Coun tr y: US A Clinic al pharmacis t e valua
tion, which included medic
ation ev alua tion, ther apeutic r ec ommenda tions t o the a tt ending ph ysician, pa tien t educ ation and f ollo w -up monit oring. DSD , SMS, DS, CIS 6 70 (R CT) GE SICA , (2005) N: 760/ 758; Ag e: 65/65; Male: 73/69 ; NYHA: NR; Coun tr y: Ar gen tina Fr equen t t elephone f ollo w -up fr om a single sur veillance cen tr e pr ovided b y nur ses tr ained in HF t o monit or and r ein for ce self -manag emen t perf ormed b y using a pr ede termined ques tionnair e. DSD , SMS, DS, CIS 16 85 (R CT) Harrison e t al., (2002) N: 92/ 100; Ag e: 76/76; Male: 53/56; NYHA: 2.9/2.8; Coun tr y: Canada The T ransitional Car e used a c ompr ehensiv e e vidence-based pr ot oc ol f or c
ounselling and educ
ation f
or HF self
-manag
emen
t
plus additional and planned link
ag es t o support individuals in t aking char ge of aspects of their c ar e giv en b y hospit al and community nur ses. DSD , SMS, DS, CIS 2.8 70 (R CT) Heidenr eich e t al., (1999) N: 68/ 86; Ag e: 74/75; Male: 58/58; NYHA: NR; Coun tr y: US A Multidisciplinar y pr ogr am of pa tien t educ
ation, daily self
-monit oring , and ph ysician notific ation of abnormal w eigh t g ain, vit al signs and s ymp toms giv en b y small pr actices (lar gely primar y car e) of a multispecialty gr oup. SMS, CIS 12 65 (CC T) Hols t e t al., (2001) N: 36/ 36; Ag e: T ot al: 54; Male: Tot
al: 81; NYHA: NR; Coun
R1 R2 R3 R4 R5 R6 R7 R8 R9 R10 R11 R12 R13 R14 R15 R16 R17 R18 R19 R20 R21 R22 R23 R24 R25 R26 R27 R28 R29 R30 R31 R32 R33 R34 R35 R36 R37 R38 R39 32 Chapter 2 Table 1: Con tinued Author , y ear of public ation Popula tion† In ter ven tion Componen ts†† Follo w -up (mon ths) Quality (s tudy design) ††† Hughes e t al., (2000) N: 981/ 985; Ag e: 70/70; Male: 97/96; NYHA: NR; Coun tr y: US A
Home based primar
y c ar e, including a primar y c ar e manag er , 24-hour c on tact f or pa tien
ts and Home Based Primar
y Car e t eam participa tion in dischar ge planning. DSD , CIS 12 60 (R CT) Kasper e t al., (2002) N: 102/ 98; Ag e: 60/64; Male: 65/56; NYHA: 2.2/2.5; Coun tr y: U SA Multidisciplinar y t
eam including nur
se c oor dina tor (monit or ed b y telephone c alls); CHF nur se (adjus ting medic ation in CHF clinic), CHF c ar diologis t (decision support f or nur ses); primar y ph ysician (r eceiv ed upda
tes and manag
ed all not CHF r ela ted pr oblems). In ter ven tion giv en during 6 mon ths. DSD , SMS, DS, CIS 6 65 (R CT) Krumholz e t al., (2002) N: 44/ 44; Ag e: 76/72; Male: 48/66; NYHA: NR; Coun tr y: US A Face-t o-face educ ation session f ollo w ed b y a t elemonit oring phase b y the nur se f or a t ot al in ter ven tion period of 1 y ear . This telephone c on tacts r ein for ced c ar
e domains but did not modif
y curr en t r egimens or r ec ommenda tions; the pa tien t learned t o under st
and when and ho
w t
o seek and access the c
ar e. DSD , SMS 12 70 (R CT) Lar amee e t al., (2003) N: 141/ 146; Ag e: 71/71; Male: 48/50; NYHA: 2.3/2.2; Coun tr y: U SA Four major c omponen ts: early dischar ge planning , pa tien t and family CHF educ ation, 12 w eek s of t elephone f ollo w -up and pr omotion of op timal CHF medic ations giv en b y a CHF c ase manag er of the hospit al. DSD , SMS, DS, CIS 3 60 (R CT) McDonald e t al., (2002) N: 51/ 47; Ag e: 71/71; Male: 63/68; NYHA: 3/3; Coun tr y: Ir eland Specialis t nur se-led educ
ation and specialis
t die
tician c
onsults
during admission, also giv
en t o pa tien t’s c ar er . In addition, pa tien ts w er e dischar ged with a le tt er t o the r ef erring ph ysician about the s
tudy and tha
t manag
emen
t of HF-r
ela
ted issues should
be r
ef
err
ed t
o the clinic or the nur
se. T elephone f ollo w -up t o ascert ain clinic al s ta
tus and discuss pr
oblems. DSD , SMS, CIS 3 55 (R CT) Na ylor e t al., (2004) N: 118/ 121; Ag e: 76/ 76; Male: 40/44; NYHA: NR; Coun tr y: US A A 3-mon ths c ompr ehensiv e tr ansitional c ar e in ter ven tion dir ect ed by adv anced pr actice nur
se (APN) including dischar