Online interventions to support
self-management of cardiovascular risk
factors
Master thesis
W - A. W. K. P. G. K. K. Karaya Master Medical Informatics University of Amsterdam
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Online interventions to support
self-management of cardiovascular risk factors
Student Medical Informatics
W - A. W. K. P. G. K. K. Karaya, BSc Meibergdreef 7 1107AZ
Amsterdam Academic Medical Center / University of Amsterdam UvA student number: 5698499
wasudewi@gmail.com
Location of Scientific Research Project
Academic Medical Centre – Department of Medical Informatics
Scientific Research Project Tutor
Tutor Dr. Niels Peek / S. K. Medlock
Faculty of Medicine Department of Medical Informatics Academic Medical Center / University of Amsterdam E-mail: n.b.peek@amc.uva.nl / s.k.medlock@amc.uva.nl
Scientific Research Project Mentor
Mentor Dr. Ronald Cornet
Faculty of Medicine Department of Medical Informatics Academic Medical Center / University of Amsterdam E-mail: r.cornet@amc.uva.nl
Scientific Research Project Duration
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Preface
This thesis provides the results of the scientific research project regarding the search for online self-management interventions that supports self-management of cardiovascular risk factors. This scientific research project is the final part of the Master Medical Informatics at the University of Amsterdam, and was conducted under the department of Medical Informatics at the Academic Medical Centre.
Conducting each part of this scientific research project and writing this thesis would not have been accomplished without the help and support of a number of persons.
Firstly, I would like to express my heartfelt gratitude to Niels Peek, Ace Medlock, and Ronald Cornet for giving me the opportunity to conduct this research project. Their illuminating instructions and valuable suggestions to keep focus while maintaining a scientific level, and stearing in the correct direction during the project was necessary to complete this thesis.
Secondly, many sincere thanks go to Sandra Vosbergen for her valuable and supportive input during the meetings. In addition, I owe gratitude to my fellow students for their support during the period of this project. Furthermore, I would like to thank Anna, who gave me wonderful comments about my work and for introducing me to Emmi. My sincere thanks go to Emmi for her help with my English and her suggestions for altering the odd Dutch phrases. Thirdly, I would like to thank all general practitioners who participated in the qualitative study and arranged their time on such short notices. Without their input in this project the difficulties of implementing the recommendations from the clinical practice guideline would have been unknown.
Finally, I would like to express my inner most gratitude to my sisters, brothers, and parents who asked each day about the progress and the future activities that came up during the project.
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Abstract
Introduction: The Dutch clinical guideline on Cardiovascular Risk Management (2006) describes the management of patients at an increased risk of cardiovascular disease (CVD). The goal of the guideline, used by general practitioners, is to prevent cardiovascular events such as myocardial infarction and angina pectoris through implementation of recommendations. However, the implementation of recommendations can be challenging as patients do not adhere to medication prescription or scheduled times. In recent years, emerging technologies such as e-health provide new opportunities to involve and motivate/encourage patients in the management of risk factors. Patients could manage their own risk factors with support of online health interventions. Which online interventions can supplement the implementation of the CVD Risk Management guideline in general practice, and support Dutch healthcare consumers in their management of cardiovascular risk factors? Methods: First, a qualitative study was conducted among Dutch general practitioners. The purpose of this study was to identify factors which enact as either facilitators or barriers for implementing of guideline recommendations. In addition, the influence of information technology on implementation. Second, inventory study was conducted to identify the online health interventions that can be used by patients with (a potential) CVD.
Results: GPs do implement the recommendations of the CVRM guideline such as tracing patients, recommending lifestyle advice, and maintaining risk profiles. However, a number of factors inhibit implementation. Patients factors such as cognitive and cultural factors are the most common factors which restrict implementation. IT supports the implementations with a number of functionalities of the electronic patient record and Edifact messages. A total of 99 interventions were found which are either related or not related to a scientific study. The largest number of interventions provide support for hypertension, obesity, and smoking. The included interventions are mainly developed in US and the Netherlands. Education, self-management, and communication is the most frequent appearing component among the included interventions. The found results are either internet based or cell phone based interventions.
Conclusion: A large number of guideline recommendations regarding tracing, identification and on lifestyle are implemented by the GPs. Nonetheless, factors related to patients and environmental inhibit implementation. Noncompliance to medication intake or absence on consultations happen to be frequently appearing factors. IT such as the electronic patient record and Edifact messages supports the implementations with a number of functionalities which include tracing and identifying patients but also maintaining the risk profiles. Patients can choose among the found interventions to manage their risk values by their own. Among the interventions a large number have been shown effective. The common found components are education, self-management, and communication.
Keywords: health interventions, cardiovascular disease, guideline implementation, qualitative research
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Samenvatting
Introductie: De Nederlandse richtlijn: Cardiovasculair Risico Management (2006) beschrijft het management van patiënten met een verhoogde kans op hart – en vaatziekten. Het doel van deze richtlijn, die gehanteerd wordt door huisartsen, is het voorkomen van cardiovasculaire events zoals myocardinfarct en agina pectoris door het implementeren van adviezen. Echter, implementatie van de adviezen kan een uitdaging zijn omdat patiënten niet houden aan het medicatievoorschrift of geplande consulttijden. In de afgelopen jaren bieden technologieën als e - health nieuwe mogelijkheden om patiënten te betrekken en te motiveren/aan te moedigen bij het managen van risicofactoren. Patiënten kunnen hun eigen risicofactoren managen met ondersteuning van online gezondheidsinterventies. Welke online interventies kunnen een aanvulling zijn voor de implementatie van de CRVM-richtlijn in de huisartsenpraktijk en ondersteunt Nederlandse consumenten in het managen van de cardiovasculaire risicofactoren?
Methoden: Ten eerste, een kwalitatief onderzoek was uitgevoerd onder Nederlandse huisartsen. Het doel van deze studie was om factoren te identificeren die facilitatoren voor of barrières zijn voor het implementeren van de aanbevelingen. Ten tweede was een inventariserende studie uitgevoerd naar bestaande online gezondheidsinterventies die gebruikt kunnen worden door patiënten met een (potentiële) cardiovasculaire aandoening is uitgevoerd.
Resultaten: Huisartsen implementeren de aanbevelingen die beschreven zijn de CVRM-richtlijn zoals het traceren van patiënten, aanbevelen van leefstijl adviezen en onderhouden van de risicoprofielen. Echter, een aantal factoren ondersteunen of verhinderen implementatie. Patiënt gerelateerde factoren zoals cognitieve en culturele factoren zijn de meest bekende blokkerende factor. IT ondersteunt de implementatie met een aantal functie van het elektronisch patiëntendossier en Edifact berichten. In totaal zijn 99 interventies gevonden die gerelateerd zijn aan een wetenschappelijke studie. Het grootste aantal interventies biedt ondersteuning voor hypertensie, overgewicht en roken. De geïncludeerde interventies zijn voornamelijk ontwikkeld in de Verenigde Staten en Nederland. Educatie, zelfmanagement en communicatie zijn de meest voorkomende componenten onder de interventies. De gevonden resultaten zijn vaak internet of mobiel gebaseerde interventies. Conclusie:
Een groot aantal aanbevelingen met betrekking tot opsporing, identificatie en over lifestyle worden uitgevoerd door de huisartsen. Echter, patiënt gerelateerde factoren remmen implementatie. Ontrouw aan medicatie inname of afwezigheid op consulten zijn vaak voorkomende factoren. IT zoals het elektronisch patiëntendossier en Edifact berichten ondersteunt de implementaties met een aantal functionaliteiten waaronder het opsporen en identificeren van patiënten, maar ook het onderhouden van de risicoprofielen. Patiënten kunnen kiezen uit interventies om hun risicowaarden te managen. Onder de interventies zijn een groot aantal effectief gebleken. De veelvuldig gevonden componenten zijn educatie, self-management en communicatie.
Key – woorden: gezondheidsinterventies, cardiovasculaire aandoeningen, richtlijn implementatie, kwalitatief onderzoek.
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1.1 Research problem
Approximately, forty thousand Dutch patients died due to cardiovascular disease (CVD) in 2010, which was roughly 30% of the deaths from all causes [1]. In the Netherlands, CVD is defined as the clinical conditions caused by the physiological process of atherothrombosis, which is an atherosclerotic plaque with a superimposed thrombosis in arteries [2]. This process leads to clinical manifestations, such as myocardial infarction (heart attack), angina pectoris (pain or pressure in the chest), cerebrovascular accident (CVA or stroke), transient ischemic attack (TIA or “mini-stroke”), aortic aneurysm (bulging of the wall of the aorta) and peripheral arterial disease (reduced circulation in the limbs) [3]. Risk factors, such as an unhealthy lifestyle (diet, physical inactivity, and smoking), age, gender or hypertension all contribute to this health deteriorating process and subsequently to one or more of the CVD endpoints.
Therefore, it is important to reduce the presence of these risk factors as much as possible [4]. Risk factor levels can be lowered through both primary and secondary prevention. The former type of prevention focuses on the prevention of diseases and the preservation of health in the individual, while the latter type prevents reoccurrences and a worsening of CVD or its complications [5]. Multiple studies substantiate the reduction of CVD burden through both primary and secondary prevention [6-9]. Preventive instructions/ activities for (CVD) patients, such as taking medication, exercising, following a diet, and managing pain or other related symptoms, are examples of self-management [10].
Multiple studies on self-management have shown improved outcomes for patients with chronic health problems [11-13], including patients with CVD [14]. Barlow and colleagues define self-management as “the individual’s ability to manage the symptoms, treatment, physical and psychosocial consequences and lifestyle changes inherent in living with a chronic condition”. In addition, effective self-management is accomplished with “the ability to monitor one’s condition and to effect the cognitive, behavioural and emotional responses necessary to maintain a satisfactory quality of life” [15]. A term related to self-management is self- efficacy. Bandura (1997) describes self-efficacy in relation to health as “a person’s confidence to carry out self-management behaviour”, such as deciding on the appropriate food choices, cessation of smoking, and sufficient exercise, resulting in a behaviour change [16].
Interventions designed for self-management of chronic illness are known as individualized behaviour change interventions. The main purpose of these health interventions is to increase self-management, control of treatment, and its effects on the quality of life [17]; other considerations should include assessment, goal setting, action planning, problem solving and a follow up component [18]. These interventions can be provided through the Internet because of its wide availability and accessibility at any time of the day. In addition, information provided via the Internet can contribute to the improvement of the patients’ understanding of their medical condition to make health decisions. A disadvantage of this delivery mode is the “digital divide” among specific patient groups including those with a (potential) CVD [19-20]. The digital divide can be described as the gap in access and understanding the use of digital technologies such as Internet [21]. Nevertheless, patients with chronic diseases do show an interest in online self-management interventions [22-23].
The management of CVD risk factors in the Netherlands is organized by the general practitioner (GP) as the responsible care provider and is supported with a clinical practice guideline named “Multidisciplinary Guideline for Cardiovascular Risk Management” (2006).
8 This guideline provides the GP with (preventive) recommendations/advice to reduce CVD risk factors and their effects on patients that could be and are at risk [24,25]. Therefore, implementation of these recommendations is necessary. However, as with other clinical practice guidelines [26,27], this specific guideline may have barriers such a lack of knowledge and factors related to patients which could inhibit CVD management.
With the growing number of (potential) CVD patients, the purpose of self-management and the possibilities of online interventions, health care providers could recommend specific online self-management interventions to their patients. In addition, these interventions could be used independently by patients, which could supplement the actions of the physician and compensate for imperfect guideline implementation.
1.2 Research goal and question
The goal of this research project is to generate an inventory of online interventions which support behaviour change of modifiable cardiovascular risk factors for (future) patients with CVD, taking into account the implementation of the Dutch Guideline on Cardiovascular Risk Management, and the experiences of GPs.
The following main research question that will be addressed in this thesis:
Which online interventions can supplement the implementation of the CVD Risk Management guideline in general practice, and support Dutch healthcare consumers in their management of cardiovascular risk factors?
In order to answer this question, it is necessary to answer the following sub questions:
1 How is the Dutch Guideline on Cardiovascular Risk Management implemented in clinical practice by GPs?
2 Which online interventions support self-management of modifiable CVD risk factors?
1.3 Research approach and thesis outline
This thesis has the following chapter outline: Chapter 2 elaborates on background information about the cause of and the associated risk factors of CVD. The results of the interviews with general practitioners about the current level of implementation of the Dutch clinical practice guideline “Cardiovascular Risk Management 2006” is elaborated in thethird chapter. An inventory study in chapter four delineates the online health interventions supporting management of cardiovascular risk factors. Chapter five provides an umbrella view of the main findings, strengths and limitations of the previous chapters, discusses future work, and provides the conclusions of this thesis.
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2.1 Cardiovascular risk factors
A number of risk factors can influence the development of atherothrombosis [28]. Risk factors associated with CVD can be grouped into: non – modifiable and modifiable risk factors. Age, gender, and family history are non – modifiable risk factors. Physiological, behavioural, and psychological risk factors are different types of modifiable risk factors. Hypertension, abnormal blood cholesterol, diabetes mellitus, and obesity are known as physiological risk factors and behavioural factors include smoking, physical inactivity, and alcohol consumption, whereas stress, depression, and coping are defined as psychological factors. The following sub sections will briefly discuss cardiovascular risk factors.
Non-Modifiable Risk Factors Age
The risk of a cardiovascular event increases as an individual ages, thus [29,30] resulting in heart attacks and strokes [31]. In addition, aging increases the risk for diabetes mellitus and the level of hypertension [32,33]. Of course, no cure exists for reducing the ills that accompanied the ageing process. However, the process of ageing can be delayed through an appropriate diet and sufficient physical activity [31].
Gender
Among western women, CVD is the major cause of death due to a prolonged life compared to men. Women, after having gone through menopause, have an increased risk for CVD. Various studies point to the reduced level of endogenous oestrogens as the cause for the onset of cardiovascular disease [34,35].
Family history
High blood pressure, diabetes mellitus, and elevated cholesterol are examples of medical conditions that can be inherited by offspring [36]. Similarly, patients with an increased risk for a stroke event or a heart attack are likely to inherit it from the prior generation [31]. Although a positive family history for CVD cannot be altered, it is possible to reduce the inherited tendencies through behavioural changes such as altering dietary behaviour and increasing physical activity. [37].
Modifiable Risk Factors
Physiological risk factors
Hypertension
A contributor to the onset of CVD is high blood pressure or hypertension [38], which could lead to coronary heart disease and heart failure. An abnormal blood pressure is strongly associated with diabetes mellitus and an abnormal cholesterol level. The possible interaction of these risk factors could result in an increased overall risk for patients with hypertension [25, 39].
Abnormal cholesterol level
Dyslipidaemia is defined by the total cholesterol [TC]. Patients with high cholesterol levels have an elevated risk of stroke, ischemic heart disease, or other heart diseases. This risk factor has causal relations with other risk factors such as family history, obesity, and diabetes [31]. Although the TC of each person rises during the aging process, women have higher
11 levels of HDL as compared to men [40]. Lifestyle recommendations such as daily exercise and a lipid lowering diet should be maintained to reduce the TC [31].
Diabetes mellitus
Among the three major types of diabetes type II is the most common. Severe complications can occur, such as heart attack, stroke, renal failure, amputations of the extremities, and occurrence of blindness with a late diagnosis of diabetes [31]. In addition, diabetes is likely to be accompanied by CVD risk factors such as obesity, hypertension, and high cholesterol [41]. Therefore, weight loss, regular exercise and an appropriate diet have a positive effect on patients with diabetes [31].
Obesity
The BMI [body mass index] is a measurement of the amount of body fat calculated in kg/m2. The risk for a CVD increases with an increment of BMI [30]. Overweight and obesity have a strong association with other risk factors, such as hypertension, elevated cholesterol, and diabetes mellitus [1,42,43]. These four risk factors combined are named the metabolic syndrome [44].
Behavioural risk factors
Smoking
Cigarette smoking could result in coronary heart disease, stroke and peripheral vascular disease [31,36]. Smoking cessation results in a lower risk of CVD. Various chemicals, such as nicotine and carbon monoxide damage the lumen of the arteries causing an increased uptake of cholesterol plaques in the arterial lumen [45]. The SCORE project states that smokers with increased cholesterol levels have a fivefold higher risk for a fatal CVD compared to non-smokers with dyslipidaemia [36,46].
Physical inactivity
Inactive persons could develop various chronic health conditions including hypertension, obesity, heart attack, or osteoporosis. All of these could eventually result in premature death [47]. Multiple findings describe the benefits of physical activity such as improvement of blood circulation, weight loss, and better regulation of insulin [48-50].
Alcohol consumption
Excessive consumption of alcohol is a risk factor for various negative health outcomes such as raised blood pressure, various heart diseases, liver cirrhosis, neuropathy, and sudden infant death syndrome. In contrast, moderate drinking can be associated with lower risk for several CVDs, including coronary heart disease, increased cholesterol, and atherosclerosis [31, 51, 52]. Alcohol increases the risk for diabetes type II [53] and the blood pressure level [54].
Psychological risk factors
Stress
Multiple scientific articles have shown the association between stress and CVD [49,55-57]. Due to stress the cardiovascular system may increase the heart rate and increase the levels of blood pressure, cholesterol, and glucose which could result in strokes. A negative lifestyle
12 is adopted during periods of stress with more consumption of alcohol, increased smoking, and other factors that support the onset of CVD [58].
Depression
A feeling of sadness, tiredness, a depressed mood and a decreased interest in activities depict the presence of depression. The contribution of depression to CVD and vice versa has been described in multiple studies [56,59,60]. Patients with a first heart infarction have an increased risk for the development of depression, but patients with depression also have an elevated risk for any type of CVD. Significant evidence shows that depression is associated with other CVD risk factors [60]. Smoking among depressed patients is increased compared to non-depressed patients. Depressed subjects are less successful in attempts to quit smoking [61]. Substantial evidence shows the association between depression and elevated cholesterol levels [62] and a higher risk for hypertension [59].
2.2 The Dutch clinical practice guideline cardiovascular risk management 2006 and the
updated version of January 2012
An optimal prevention policy with respect to the treatment of patients with an elevated cardiovascular risk is the main objective of this guideline. A treatment should result in sufficient reduction of the complications and reduced incidence of a first or new CVD event. This guideline focuses on patients with a (potential) increased risk for CVD and assumes that the population consults the general practitioner or other care providers for a specific reason related to CVD. Neither tracing (patients need to be traced to be included in CVRM management) nor screening for risk factors are part of this guideline. Patients with an elevated risk for a first or new manifestation of CVD are provided lifestyle advice and coaching/counselling. A CVD is caused by an atherothrombotic process leading to clinical manifestations
Identification of patients with an increased risk of CVD
Patients are divided into two groups: patients with CVD or DM2 and those without CVD or DM2. Subjects of the first group have an increased risk of progression of illness and new events. Patients of the second group are those with symptoms, a family history of premature CVD, visible overweight, or a specific request for information about risk factors. A risk profile is required in cases of a systolic blood pressure ≥ 140 mmHg, TC ≥ 6,5 mmol/l; and smoking behaviour among men ≥ 50 years or women ≥ 55 years of age. The 2012 update include patients with Rheumatoid Arthritis (RA) as a group because of the notable increase in risk of a future CVD event [25].
Diagnostics Risk profile
A risk profile should contain the following risk factors: age, sex, smoking, systolic blood pressure, cholesterol levels, glucose level, family history (before 60), diet, alcohol use, physical activity, BMI and waist circumference. The 2012 update underlines additional attention for immigrants regarding family history and adds elevated serum creatinine level as a risk factor [25].
13 Risk assessment
Patients without CVD and without diabetes mellitus type II (DM2) can, based on the data from the risk profile, assess their ten-year risk of developing fatal CVD using the SCORE risk table. The table has the risk factors: age, smoking, hypertension, and the cholesterol level, incorporated to assess the ten-year risk. The percentages provide an indication of the risk of death due to CVD and estimate the effect of changes in the risk profile. The values for blood pressure and lipid are applicable regardless of the usage of pharmaceutical treatment.
Four adjustments were made in the updated version regarding the SCORE risk table. Firstly, this table assesses the ten-year risk of illness due to a CVD. Secondly, the risk of patients with DM or RA can be estimated by adding 15 years above the actual age. Thirdly, the table does not focus on those patients with a previous CVD manifestation. Fourthly, patients with an age above 65 can estimate the ten-year risk of illness or death due to a CVD [25].
Treatment
The decision for the treatment should be in consensus with the patient, taking into account the level of CVD risk and the specific circumstances of the patient. The choices made for treatment should lead to the desired effect and subscribing to prolonged adherence. Patients can be coached through referral to various health care providers.
Non – pharmacological treatment focuses on altering lifestyle behaviour through recommendations such as smoking cessation, nutrition instructions, and moderate alcohol consumption. The updated guideline recommends preventing or recognizing stress in an early phase by providing suitable interventions [25]. Patients can receive pharmacological treatment depending on the presence of a CVD. For additional reading about the non – pharmacological and pharmacological treatment for each CVD risk factor see [25].
Follow up
A number of repetitive visits are recommended for each patient for a continuous positive effect of the non - pharmacological treatment and pharmacological treatment. The health care provider needs to assess the patient for compliance to lifestyle recommendations, evaluate treatment of the drug effects and check the risk profiles of patients with a pharmacological treatment. Patients with CVD need stricter follow up recommendations compared to patients without CVD.
This chapter elaborates background information about the Dutch clinical practice guideline CVRM (2006) providing recommendations and advice for GPs regarding care for patients with CVD that should be implemented in practice. In the following chapter we investigate Dutch general practitioners' implementation of this guideline.
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Chapter 3 – Qualitative study: Implementation of the Dutch
CVRM guideline among general practitioners
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3.1 Introduction
Guideline implementation is important as it supports health care providers with diagnostic and therapeutic decisions and improves the quality of care [63]. Moreover, patients have the possibility to reduce their mortality and morbidity and enhance their empowerment and quality of life [64, 65]. Implementation refers to active dissemination of information which overcomes barriers using proper and effective strategies [66]. Dissemination can be defined as distribution of information and the practitioners’ natural, unaided adoption of policies and practices [66].
Multiple factors either support or inhibit implementation. The work of Abrahamson and co-workers elaborates on factors which support implementation of guidelines [71]. However, various studies focus on factors which facilitate the implementation of clinical practical guidelines, including the Dutch CVRM clinical practice guideline 2006 [67-70]. The conceptual framework of Cabana defines a barrier as any factor that limits or restricts complete implementation of a guideline. This framework consists of three main categories of barriers: barriers related to knowledge, barriers related to attitude, and external barriers, which are divided in sub-categories [67]. A possible solution to overcome these barriers is the use of Information Technology [72].
A method to identify the current facilitators and barriers for this clinical practice guideline is through interviews [73]. In investigating adherence to the Dutch CVD guideline, these interviews should be conducted with the GPs as they are the primary care providers of Dutch patients and are thus responsible for implementing many of the recommendations of the guideline. For these reasons, this chapter presents a qualitative study of interviews with GPs regarding the adherence to the recommendations/advice of the Dutch CVRM clinical practice guideline 2006. The goal of this study is to gain insight in the implementation of the Dutch clinical guideline CVRM 20061 among GPs.
Research question: To what extent do GPs believe the Dutch clinical practice guideline Cardiovascular Risk Management 2006 is implemented in their practice?
In order to find an answer for the research question, the following sub-questions need to be studied:
• How do the GPs implement the CVRM guideline in clinical practice?
• Which facilitators and barriers are perceived with the implementation of the clinical practice guideline?
• How does the use of IT influence the implementation of the guideline?
3.2 Methods
The research questions were approached by conducting interviews with Dutch general practitioners.
1
Although, this study was conducted with the version of 2006, at the moment of conducting this study the updated version (2012) of the CVRM clinical practice guideline was released during the study.
16 Recruitment
All GPs from Utrecht, the Netherlands, were considered eligible to participate in this
qualitative study. A total of 16 GPs received telephone calls, an email, or both to inform them about the purpose of the study to request their participation.
Interview questions
The main purpose of the interviews was to retrieve information about the implementation of the clinical practice guideline in his/ her practice. This resulted in three sub-goals, and thus three main topics for the interviews. Firstly, it was important to understand if and how GPs apply each guideline topic in their practices. The second goal was understanding the reasons for reduced or lacking of implementation. As IT systems support the current workflow of GP practice, the third goal was understanding the influence of IT on implementation. An expert in medical informatics and guideline implementation (NP) defined the domains and suggested concepts. Topics for the domain CVRM were derived from the sections of the multidisciplinary guideline CVRM, and topics for the domain Guideline implementation were derived from the barriers defined by Cabana [67] and the equivalent facilitators were set as concepts. An initial version of the interview questions was developed by the primary researcher (WK). The topic guides containing the interview questions were reviewed by the domain experts (NP and SV) and revised iteratively until agreement was reached.
Interviews
Face-to-face Interviews were conducted by one researcher (WK). An informed consent was obtained from all participants to audiotape the conversation before conducting the interview. If no new findings arose for a topic after 5 consecutive interviews, the topic was considered saturated and was not discussed in subsequent interviews. Each interview was transcribed verbatim and sent to the participants for comments and/ or corrections.
Analysis
Coding of phrases is an important process to analyze the content of the interviews. Codes can be defined as tags or labels for assigning units of meaning to the descriptive or inferential information compiled during a study. Codes can be obtained based upon theories or concepts (theory-driven), derived from raw data (data-driven) or from research goals (structurally-driven). A set of codes, definitions and examples supporting analyzing interview data is defined as a codebook [74]. For this study we developed two codebooks using a combination of a theory and data-driven approaches, and a third using a purely data-driven approach.
The first codebook focused on the Dutch clinical guideline CVRM. Hence, the first code set contains primarily code labels similar to the domain of the topic guide. A CVRM code was assigned to each phrase in case of information referring to a concept of CVRM. The different facilitators of and barriers for the implementation of the guideline are classified in the second codebook named “Guideline Implementation”. The conceptual framework of Cabana was applied to the remarks to determine the barriers of implementation [67]. We defined facilitators as the opponent categories of the framework of Cabana. Therefore, a facilitator can be defined as any factor which enhances or supports (complete) implementation of the guideline. Apart from the theory-driven codes, additional codes were abstracted from the data during meetings with the domain experts, after the interviews. Finally, a codebook for remarks about information technology used to support the management of CVD patients was developed using a data-driven approach.
17 Coding was performed in two steps. First, phrases in the transcript were identified that were relevant to one of the three goals, based on the following criteria:
Goal 1: understand if and how GPs apply each guideline topic in their practices • whether and how GPs implement recommendations in their practices
• descriptions about management of a risk factor and other health care providers’ involvement with CVRM
Goal 2: understanding the reasons for reduced or lacking of implementation
• actions/tasks which supports or inhibit implementation or factors that affect implementation
Goal 3: understanding the influence of IT on implementation • Comments about the use of IT for recommendations.
In addition, phrases referring to a specific (sub) concept of the codebooks were also marked for analysis. The second step was the coding procedure. Phrases were assigned one or more codes from the three codebooks with a maximum of one code per codebook. In case of no match, the codes were labeled as “other”. The phrases with the label “other” were subsequently labeled with data-driven codes, which were assigned when multiple phrases covered a similar (sub)concept or a new concept was derived related to one of the goals. The label “noise” was assigned to comments that were not relevant to any of the three goals. In addition, data-driven codes were assigned for multiple phrases covering a similar (sub) concept. For four transcripts, phrase selection and coding was performed by the primary researcher (WK) and the domain experts (NP and SV). During meetings, the selected phrases of the transcripts were compared and discussions were held in case of different results/opinions until agreement was reached. The selection and coding of the remaining five interview transcripts were conducted only by the primary researcher.
3.3 Results
Participants
A total of 16 GPs were informed about the study, whereof nine GPs (eight males, one female) replied for an interview. The remaining GPs said they were not interested in participating or did not respond to the invitation. Among the participants, four GPs work as a solo practitioner in their practice, while the others work in a group along with other GPs. The majority of the GPs have been practicing their profession for over 20 years. The interviews were conducted in Utrecht, from the end of January 2012 to the beginning of March 2012 at the practice of each GP, and each interview lasted between 15 to 40 minutes.
Interview questions
The interviews were supported with an interview guide which contains questions about the different CVRM topics. Other questions focused on limited or no implementation of a recommendation and the reason behind it. We asked specifically about the information technologies supporting implementation. Appendix A – Topic guide table presents topics discussed and the questions asked during the interviews.
18 Appendix B – Codebook CVRM provides a table with the derived concepts and sub-concepts along with definitions and codes. An additional 20 data-driven codes were added, including one concept, “Tracing Patients”. Appendix C contains the Codebook Guideline Implementation. To the framework of Cabana, we added three categories of facilitators: “Facilitators Related To Knowledge”, “Facilitators Related To Attitude”, and “Facilitators Related to Behaviour”. An additional 15 data-driven codes were added to this codebook. The Codebook Information Technology is given in Appendix D. A total of 285 phrases were selected and labelled with codes. These consisted of 281 phrases with a code from the CVRM codebook, and these same phrases were also labeled with another code from the Guideline Implementation codebook as either a facilitator or a barrier. The remaining 4 phrases were labeled as a Future Objective. The “Information Technology” label was assigned 39 times.
Analysis
A total of 281 phrases were identified and assigned with to two or three codes. The analysis starts with the results of the CVRM concepts and are organized by topic according to the topic guide (see Appendices A, B, and table 3.1). The analysis continues with followed by the found facilitators and barriers (see Appendix C and table 3.2), and ends with the information technologies used for implementation (see Appendix D and table 3.3).
CVRM in general (16 comments)
The clinical practice guideline provides specific information and recommendation/ advice to manage the health conditions of patients with and without CVD. It is developed for health care providers including GPs. Each interviewed GP acknowledged the existence of this guideline and expressed their awareness of the recommendations, for example:
“No, [I have no problems] with the content of [the guideline] because, I work for ten years according to the guideline.” Codes: Guideline Implementation/Facilitator/Physician Behaviour/External Facilitators/GuidelineRelatedFactors
A GP should disseminate the recommendations to patients with an increased risk for CVD. Eight of the interviewed GPs organize consults for CVRM and communicate with patients about recommendations. However, two practices are not able to arrange consults for CVD patients due to various reasons such as lack of time and financial resources.
“The GPs have no CVRM consultation yet but, we are thinking about it.”
Codes: Guideline ImplementationI/Barrier/Physician Behaviour/External Barriers/Lack Of CVRMConsultingTime
Except for one GP, all the participants use information technology for CVRM and subscribe to its benefits.
“With the EPR a lot of CVRM work can be accomplished” Codes: Information Technology/ElectronicPatientRecord
Individuals with an elevated risk for CVD and other patient groups need to be identified. Patients with a CVD, DM2, an inherent disposition, or who smoke are examples of patient’s groups that should be included. Six out of nine GPs identify their patients with the ICPC codes and/ or health indicators (in Dutch: ruiters) which are linked to patients records in the electronic patient record. Two other GPs did not mention how patients are identified while one participant use paper cards instead. No remarks were made about identification of patients with and without CVD or DM2. In addition, none of the GPs referred to identification of patients with an elevated cholesterol. Environmental factors such as financial problems and work overload were cited as barriers to identifying patients.
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Tracing patients (19 comments)
The guideline recommends that patients need to be traced to be included in CVRM. The participants mentioned two types of tracing: active and passive tracing. A practice may inform patients about CVRM interventions through sending invitation letters or other activities. This is called active tracing.
“The practice announces in the waiting room and on the website that specific patient groups are invited for screening programs.” Codes: CVRM/Tracing Patients/Tracing For Inclusion
Passive tracing or case finding as suggested by the guideline recommends tracing of CVD patients during regular consultations. Seven GPs apply the passive tracing strategy in their practice. The other two participants apply the opposite type of tracing.
“To invite patients, systematically, requires funding.” Codes: Guideline Implementation/Barrier/External Barriers/Physician Behaviour/Environmental Factors/Lack Of Finances
Identification of patients with elevated risk for CVD (24 comments)
Patients with a CVD, DM2, genetic predisposition or who smoke are examples of patient groups with an elevated risk that should be identified. Six out of nine GPs identify their patients with the ICPC codes and/ or health indicators which are linked to patients’ records in the electronic patient record. Multiple Dutch electronic patient records such as Omnihis and MicroHIS X contain a module which supports the extraction of this kind of data through queries [75].
“A query is entered in the electronic patient record to obtain patients with specific ICPC codes. Searching patients with CVD characteristics is conducted every two years.” Codes: Guideline Implementation/Facilitator/Physician Behaviour/Use Of Information Technology
Two other GPs did not mention how patients are identified while one participant used paper cards instead. No remarks were made about identification of patients with and without CVD or DM2, or identification of patients with an elevated cholesterol. Seven of the nine GPs do not track smoking in relation to CVD risk.
“I do not know whether a patient smoke.” Codes: Guideline Implementation/Barrier/Physician Attitude/Lack Of Implementation Of Recommendation
“The care providers do not identify patients who smoke and are 50 years and older.” Codes: Guideline Implementation/Barrier/Physician Attitude/Lack Of Implementation Of Recommendation
Risk profile (37 comments)
A complete risk profile should be obtained with all the values of each risk factor such as smoking, systolic blood pressure, and lipid spectrum. Eight GPs enter the values of the risk factors in their electronic patient record system.
“The care providers enter health values in the electronic patient record and create a risk profiles with a standardized set of measured values.” Codes: Guideline Implementation/Facilitator/Physician Behaviour/Use Of Information Technology
The glucose levels, cholesterol levels, and blood pressure are managed by each practice. Two GPs do not register the waist circumference. One GP gave the reason that this risk factor lacks additional information to determine a treatment. The other GP stated that the waist circumference is not present as a risk factor in the risk profile in the electronic patient record. Barriers to management of smoking cessation and measurement of the waist circumference were mentioned in 5 phrases.
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Diagnostic Procedures (10 comments)
Specific instructions for measuring the blood pressure are provided and additional laboratory tests can be performed for DM and cholesterol. No remarks were made on applying the specific instructions for blood pressure measurement. However, two of the GPs performed a screening measurement for each new patient or those that smoke to determine whether the patient has an elevated CVD risk.
“The blood pressure is measured of each new patient.” Codes: Guideline Implementation/Facilitator/ Preventive Consult
Assessment of CVD risk (13 comments)
The SCORE risk table is an assessment tool that allows providers to estimate the risk for CVD patients based on the values of TC, blood pressure, gender, age, and smoking history. The table predicts the ten-year risk of developing a fatal CVD. Seven GPs confirmed applying the SCORE risk tables in their practices. Two reasons were given: to inform patients about the consequences of the current health status (5 GPs) and/or decide to start medication to reduce the effect of risk factors (3 GPs).
“The SCORE risk table is used to inform patients if they want to know more about this instrument/.” Codes: CVRM/Assessment Of CVD Risk/SCORE Risk Table/InformationTool
“I use the SCORE risk table to determine whether a patient need to start with medication.” Codes: CVRM/Assessment Of CVD Risk/SCORE Risk Table/DeterminationForMedication
Treatment (11 comments)
The decision to start a treatment should be in consensus with the patient. A treatment should lead to the expected result and encourage adherence. CVD treatments can be pharmaceutical or non-pharmaceutical. Patient and guideline factors were mentioned as barriers to implementation.
Non-pharmaceutical treatment (68 comments)
Lifestyle recommendations are given for each modifiable risk factor such as cessation of smoking, reduction of weight, sufficient physical exercise, adequate healthy nutrition, and reduction of alcohol consumption. Each GP provides advice about lifestyle recommendations to their patients.
“Patients that smoke, I recommend them to consult a to quit smoking program.” Codes: Guideline Implementation/ /Physician Attitude/Implementation Of Recommendations
“Being overweight is a big problem. A GP informs the patient about that the increased level of glucose is unhealthy and may reduce the number of medications after weight reduction.” Codes: Guideline Implementation/Facilitator/Physician
Attitude/Implementation Of Recommendations
GPs refer patients to other primary care providers (such as a dietician, services on exercise and weight reduction, the physical therapist, and the nurse practitioner) or to secondary care. Most barriers in this category were patient factors. Four GPs stated that patients do not adopt the recommended lifestyle advice. Five out of nine GPs mentioned the referral system Zorgdomein, which supports GPs with generating referral letters for patients to specialized care institutes including hospitals [76]. Another information technology used by the GPs was the interchange of electronic data via Edifact messages. Laboratory test reports which were conducted in the hospital are sent to the GPs using this technology [77]. Each GP with an electronic patient record can use Zorgdomein and receive Edifact messages.
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“The GPs refer via Zorgdomein, frequently. These referrals cover 60 to 70 percent of all referrals.” Codes: Information Technology/ReferralSystem
Pharmaceutical treatment (25 comments)
The guideline provides instructions for medication usage for patients with CVD and/or DM, as well as those with other CVD risk factors. In addition, therapies for lowering the blood pressure and cholesterol values are described in the guideline. Five GPs stated that the medication needs to be adjusted when risk factors change, or depending on the cause of a health problem.
“I explain the recommendations of the guideline along with the benefits and limitations and let the patient decide for continuation of the treatment” Codes: Guideline Implementation/Barrier/External Barriers/Physician Behaviour/Patient Factors
According to six GPs, a number of patients do not follow medication instructions resulting in reduced or no compliance. Four participants cited a cognitive reason and/ or a cultural motive as the causes of reduced compliance. To increase compliance, these GPs repeat the recommendations and along with their benefits to their patients. Seven GPs mentioned that the final decision on treatment depends on the motivation of the patient. The GPs describe different activities to improve medication compliance. One GP stated that the electronic patient record shows when a patient did not ask for medication. Another GP invites patients to discuss their noncompliance. Each month, patients are invited to collect their medication sheet and visit the pharmacy for their medication. The non-responders are invited again on annual basis, and in the cases of no response the sheet is marked as objector or absentee.
Follow-Up (58 comments)
In order to maintain a continuous positive effect of the lifestyle recommendation and medical treatment, a follow up is clearly necessary. An individual maintenance schema should contain the important risk factor information, co-morbidity and personal wishes. An important aspect of follow-up is compliance with treatment and stop-smoking advice. During the follow-up consultation, an evaluation of the treatment should be carried out. The guideline recommends measuring fasting glucose at least three times per year. However, participants stated that two follow up consultations are organized for this risk value. Patients are invited to check their values every three months (4 GPs), or a number of CVD risk factors are evaluated once or twice a year with a health provider (6 GPs). Glucose, blood pressure and cholesterol management were mentioned. A number of patients do not respond to an invitation for the follow up. GPs were asked about the response in their practice along with the reasons for their absence.
“The care providers call patients for a follow up consultation. Although the majority of the patients do respond, a small number do not want the follow up. This group will come eventually but not for the follow up.” Codes: Guideline Implementation/ Barrier/External Barriers/Physician Behaviour/Patient Factors
“I have tried to find out the reasons for no show during the follow up via questions asked by the assistants and practical nurse. Patients answers were: forgotten, did not think about it, I thought I was not at risk, or I am still young and am not at risk.” Codes: Guideline Implementation/Barrier/External Barriers/Physician Behaviour/Patient Factors
Future Objective (4 comments)
A GP mentioned a plan to assign an assistant to checking if every patient has attended an annual follow up consult. Two participants mentioned the intention to initiate CVRM consultation and elderly consultation with a focus on CVRM recommendations in the future.
22 Another GP stated the intention to start measuring the waist circumference instead of the regular weight.
Facilitators for CVRM guideline implementation
Of the 281 phrases, 220 were identified as facilitators. The frequency of each facilitator in relation to topics from the CVRM guideline is summarized in table 3.1. The code ‘CVRM’ was used for general comments pertaining to the whole CVRM guideline. The CVRM topic with the highest frequency of facilitators was Treatment. The code ‘Implementation of recommendation’ was used when a physician indicated that one or more recommendations were implemented in his or her practice.
Code for facilitators
CV RM T raci n g P a ti e n ts Id e n tif ic a tio n O f P a ti e n ts R is k P ro fil e D ia gnos ti c P ro ced u res A ssessm en t O f CV D Ri s k T reat m en t Fol low U p Total Physician knowledge Familiarity Awareness Physician attitude Implementation Of Recommendation 2 15 9 1 55 3 85 Self-Efficacy Outcome Expectancy
Motivation/Inertia of Previous Practice Physician Behaviour
Identification Of Patients 11 6 2 19
Support Of Information Technology 2 2 6 10 1 6 27
Control Consultation 1 3 13 36 53
Provide Additional Information 10 10
CVRM Consulting Time 1 1
Preventive Consult 1 1
External Facilitators
Guideline Related Factors 1 1 2
Patient Factors 1 11 8 19
Environmental Factors 1 1
Alternative Work Environment 1 1
Financial Impulse 1 1
Total 8 16 14 26 10 12 85 49 220
Table 3.1:Frequency of facilitators categorized for each CVRM concept
Barriers of CVRM guideline implementation
Of the 281 phrases, 61 were coded as a barrier and categorized within the three main categories of Cabana and (data-driven) sub-concepts. The frequency of each barrier in relation to topics from the CVRM guideline is summarized in table 3.2. Barriers were also mentioned most frequently in association with the CVRM concept ‘Treatment’. The GPs mentioned cultural and cognitive reasons (‘Patient-related factors’) as barriers to implementing guideline recommendations relating to treatment and follow-up, particularly medication adherence and showing up for follow-up appointments. ‘Guideline-related factors’ included the complexity of the guideline.
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Code for barriers
CV RM T raci n g P a ti e n ts Id e n tif ic a tio n O f P a ti e n ts R is k P ro fil e D ia gnos ti c P ro ced u res A ssessm en t O f CV D Ri s k T reat m en t Fol low U p Total Physician Knowledge Lack Of Familiarity Lack Of Awareness Physician Attitude Lack Of Implementation Of Recommendation 1 2 5 2 10
No Need To Use The Guideline 1 1
Lack Of Agreement With Guideline Recommendations
1 1 2
Lack Of Self-Efficacy 1 1
Lack Of Outcome Expectancy 2 2
Lack Of Motivation Inertia of Previous Practice
0
Physician Behaviour 0
Reduced Use And Support Of Information Technology
1 1
External Barriers 0
Guideline Related Factors 2 1 9 12
Patient Factors 1 1 1 10 5 18
Environmental Factors 2 5 1 8
Lack Of Finances 3 3
Lack Of CVRM Consulting Time 1 1
Work Overload 2 2
Total 8 3 10 11 0 1 19 9 61
Table 3.2: Frequency of barriers categorized for each CVRM concept
Information Technology used in CVRM guideline implementation
A total of 39 phrases were labeled with a code from the Information Technology codebook. The majority of phrases are affiliated with the Electronic Patients Record followed by the Referral System and Electronic Data Interchange. The majority of phrases are affiliated with the Electronic Patients Record followed by the Referral System and Electronic Data Interchange. Table 3.3 presents the frequency of phrases about information technology per CVRM concept.
Code for information technology
CV RM T raci n g P a ti e n ts Id e n tif ic a tio n O f P ti t R is k P ro fil e D ia gnos ti c P ro ced u res A ssessm en t O f CV D Ri k T reat m en t Fol low U p Total Information Technology 1 1
Electronic Patient Record 3 3 8 13 1 28
Referral System 5 5
Electronic Data Interchange 3 2 5
Other 0
Total 3 3 8 17 1 0 7 0 39
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3.4 Discussion
The main purpose of this study was to gain insight in the implementation of the Dutch CVRM 2006 clinical practice guideline among GPs in Utrecht, the Netherlands. In addition, the facilitators for and barriers to implementation were investigated through interviews, along with the influence of IT on the implementation.
Main Findings
Eight of the nine GPs said that they conduct CVRM consultation in their practices. Eight GPs use an electronic patient record for CVRM. Passive tracing strategy described in the guideline is applied by a number of GPs to trace patients for CVRM. Identification of patients is performed with support of the electronic patient record by assigning codes/ indicators in patients’ records which can be queried. However, GPs do not identify specific patient groups, such as those above 50 years with a smoking habit. A risk profile is mainly maintained in the electronic patient record for each risk factor with the exception of smoking and waist circumference. Three of GPs used a paper based SCORE risk table to inform and treat their patients. Lifestyle recommendations were recommended by each GP. Patients are referred to various specialized care providers for lifestyle improvement. The system Zorgdomein ensures referral to these providers while Edifact messages send results/progress of the patients’ health status to the GP. Non-adherence to medication appears in each practice of the participants, even though multiple activities are organized to improve medication intake. Every three months or annually patients are invited for a follow-up consultation to manage their risk factors. However, similar to the problem with adherence to medication, a number of patients do not attend these consults, for various reasons. The codes for implementation of recommendations, control consultation, and support of information technology were the common facilitators found. The most common barriers were related to patient-related factors, guideline-related factors, and lack of agreement with guideline recommendations.
Comparisons with other studies
A reason for the awareness of the guideline among Dutch GPs could be the membership of a large number of GPs with the Dutch College of General Practitioners (NHG in Dutch), which develops guidelines including the CVRM guideline by GPs for GPs. Furthermore, “lack of knowledge” was not identified as a barrier for implementing the CVRM guideline recommendations. A 2009 study in the Netherlands [70] about the implementation of clinical guidelines such as “Cerebrovascular accident” and “Transient ischemic attack”, also found that GPs are aware of and have knowledge about CVRM guideline recommendations. A number of factors impede the implementation of the guideline. In line with the findings of our study, Moulding et al. in 1999 also found lack of finance and lack of time as factors inhibiting the implementation of recommendations [78]. Regarding patient factors, a number of GPs indicated that a patient could decide to not follow the suggested advice/treatment. Patients’ resistance regarding accepting guideline recommendations is described in the work of Gravel in 2006 in similar practices [79]. GPs mentioned having difficulties with the guideline due to its complexity and work overload in the case of a large number of patients. In a study in Ireland in 2006, Graham and colleges state that the guidelines for CVD patients should to be simpler and easier to use [80].
IT tends to be an important factor in the practice of the GP regarding implementation of the guideline recommendations. The electronic patient record is used to create CVD risk profiles and to enter queries to find patients with certain health characteristics. In addition, the referral system Zorgdomein is a system frequently used among the GPs to maintain a
25 risk profile or to refer patients to other specialised care institutions. Another important information technology is the interchange of electronic data which electronically delivers hospital reports to the practices. The impact of IT on GPs has been previously described as positive regarding the implementation of clinical evidence from a clinical guideline [72].
Strengths and limitations
One of the strengths of this study is the qualitative approach, which made it possible to capture the perspectives of GPs regarding the guideline topics which were not considered before the research. The study focussed on a single clinical practice guideline in comparison to other studies such as [70,81] which limits the possible overlap among and discrepancies between guideline recommendations. Another strength concerns the variety of solo and group practices among the interviewed participants. In this respect, the included participants reflect the GP practices in the Netherlands. The topic guide along with the initial development of the CVRM and guideline implementation codebooks were conducted by the main investigator, the PhD student and the primary researcher and later on discussed for improvement. This approach of document development reduces the risk of bias due to differences in perceptions and interpretations, in contrast to development by one researcher. The coding process was supported by two types of coding categories: theory-driven and data-driven. The first type of coding category allows a researcher to compare the results with other studies while the second type of coding prevents discarding of relevant results that cannot be classified into the first category. Another significant strength is the use of three codebooks instead of a single codebook, allowing the same phrase to be coded along multiple dimensions. Multiple codebooks allow reflection on different aspects of the obtained information. The framework of Cabana and co-workers was applied and extended to assign codes to phrases that describe barriers and facilitators. Before assigning these codes, all phrases related to our three goals were identified.
This study has several limitations. The sample of the cohort was rather small, with nine GPs, to extrapolate the result to other Dutch GPs. Furthermore, in the cohort were eight male GPs which is probably not representative of other parts of the Netherlands. In addition, this study focuses only on GPs, yet, other health care providers are allowed to implement the CVRM recommendations. Furthermore, each of the GPs say they implement the guideline recommendations. However, this may not represent the actual practice. Some facilitators do not act as factors facilitating the implementation, but act rather as solutions to barriers. Selection of relevant phrases, assigning codes, adapting the codebooks in this study was partly done by only one researcher, which may have decreased the reliability. In case of multiple researchers, topics will be discussed with different perspectives and will be interpreted in various manners. Hence, the reliability of the analysed data could increase with more researchers.
Implications and impact
The findings from the interviews gave insight into if and how GPs implement the clinical practice CVRM guideline recommendations, the factors which either act as a facilitator or a barrier for implementation and the supporting information technologies. These findings have several implications on implementation of recommendations. Lack of finance for CVRM was mentioned as a barrier. The health policy makers can, based on this comment, create a proposal to adjust the current policy of health management for CVD patients through funding. Two GPs mentioned that the waist circumference is not measured due to no functionality in the electronic patient record and reduced belief in measuring this value. This functionality
26 can be added to the EPR systems. To address the problem of belief in the value of measuring waist circumference, clinicians could be provided with links to current evidence. Patient factors regarding follow up and medication intake are frequent barriers. Health policy makers could facilitate education or information sessions for patients, preferably in various languages, to help them understand the consequences of failure to attend follow up consults or non-adherence to medication. In addition, the route of exchanging information among the care providers should be defined and processed in the information technologies. As each care provider is informed about the current health status, patients can be informed and motivated by different health providers at each type of consultation about specific recommendations. Software developers for information technologies which support health care providers could focus on the functionalities which need to be added or altered to identify different patient groups and to ensure complete management of the risk profile and follow up. Development of these functionalities should be conducted with consent of the care providers. Apart from adjusting the information technologies of health care providers, developers can focus on the development of software for patients which interacts with information technology of the GP and other care providers. A software system for the management of the patients’ own health linked with the electronic patient record may increase the empowerment of health care consumers.
Future work
Future research should investigate the implementation of the updated version of the 2012 guideline in order to determine whether the update between the versions results in an improved implementation. In addition, further research could focus on type of practice, working hours and geographical differences with a larger cohort to compare GPs and their management for CVD patients. As multiple health care providers in and around the practice are involved with CVRM, it could be useful to include them for study. These care providers may have different opinions/ interpretations of the recommendations. The information technologies found in this study and other work have been mentioned as a positive influence on the implementation. In future, a practice might be completely supported with information technology. Therefore, research could focus on information technology used by GPs and other health care providers and its influence on implementation of CVRM recommendations. Research could also investigate patients’ use of specific information technology, whether or not in combination with another information technology, that may influence the implementation.
3.5 Conclusion
This research qualitatively investigates the implementation of the Dutch CVRM clinical practice guideline 2006 recommendations by GPs. The interviewed GPs do implement a large part of the content of the CVRM guideline. However, a number of factors inhibit the implementation. Patient factors such as lack of compliance with medication and being absent during follow up consultation were commonly-mentioned barriers. IT solutions, such as the electronic patient record, emerge as an important factor facilitating implementation of guideline recommendations, as several technologies provide support for different guideline sections. In the coming chapter, an inventory research will be conducted to identify online interventions for patients which may help to solve the barriers found in this chapter.
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Chapter 4 - An inventory study of e-health interventions for
cardiovascular risk factors
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4.1 Introduction
The benefit of applying the recommendations from the Dutch clinical practice guideline CVRM 2006 would lead to an improved health situation and increase the life expectancy [25]. However, multiple industrialized countries lack implementation of these guideline recommendations to modify lifestyle behaviour leading to increased risk factor levels which could result in various CVDs [82, 83].
Individualized behaviour change interventions or health interventions supporting self-management of lifestyle recommendations and can be provided via the Internet [15]. A term related to health intervention is e-health and is a growing area of research [84-86]. E – health can be defined as the use of emerging information and communication technology, especially the Internet, to improve and enable better health and health care [87].
According to Ward and co-workers, a health intervention for CVD patients should have eight components. An intervention should provide an education module in order to learn about health topics. Self-management of the risk factors by patients should be possible and communication with health care providers and fellow patients should be facilitated. A patient need to be supported in case of a clinical change resulting in an adjustment of medications along with adherence to prescribed medicine [88]. Other important and necessary features of such an intervention are the management and maintenance of an altered lifestyle and support for coping with the symptoms of the chronic diseases [89].
In the previous chapter multiple barriers were found, such as environmental barriers and the patient’s medication compliance, for the implementation of the Dutch CVRM guideline recommendations. A health intervention supporting individual behaviour change might be a solution to these barriers. Therefore, the purpose of this chapter is to present an overview of online health interventions which could support patients with the management of CVD modifiable risk factors.
This chapter will focus on interventions for at least one of the following risk factors: hypertension, elevated cholesterol levels, nutrition, smoking cessation, alcohol consumption, stress, or depression. Another common known modifiable risk factor is diabetes mellitus. However, this risk factor is excluded from this study as the management of diabetes mellitus is well defined in other clinical practice guidelines [25]. Additionally, health interventions focusing on physical inactivity are not part of this research as there are multiple reviews describing this risk factor online [90 – 92,]. Although medication non - adherence is not defined as a risk factor, it could lead to an increased CVD risk and a significant burden to health care [93]. Moreover, non-adherence has been documented to occur in at least 60% of cardiovascular patients [94]. Research has shown that high adherence leads to a significant reduction of cardiovascular risk [95-96]. Therefore, interventions focusing on medication adherence will be incorporated as a risk factor in this study. The research objective of this chapter is to identify existing e-health interventions that support the management of these modifiable CVD risk factors.
