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Evaluation of Feasibility of 2 Novel Heart Failure Monitoring Instruments to Facilitate Patient Recognition of Symptoms

Wakefield, Bonnie PhD, RN; Groves, Patricia PhD, RN; Drwal, Kariann MS; Scherubel, Melody BSN; Kaboli, Peter MD, MS

The Journal of Cardiovascular Nursing: January/February 2016 - Volume 31 - Issue 1 - p 42–52
doi: 10.1097/JCN.0000000000000213
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Purpose: To maintain clinical stability, patients with heart failure (HF) must recognize often subtle but clinically significant symptoms that can precede decompensation. The primary objective of this study was to evaluate the feasibility of 2 patient self-monitoring instruments designed to facilitate both HF symptom recognition and reporting of these symptoms to providers. Secondary goals included assessment of actions taken by patients when their symptoms indicated potential HF decompensation, changes in self-care management, and patients’ perceptions of the usefulness of the instruments in symptom monitoring.

Methods: A pretest-posttest longitudinal design was used for the study. Data were collected at a Midwestern Veterans Affairs Medical Center. Participants used 2 paper-based graphs to monitor weight and dyspnea daily for 3 months. The participants were interviewed at baseline about self-care activities and, at study completion, about perceptions and use of the graphs. The Self-Care of HF Index was administered at baseline and completion to assess for changes in self-care.

Results: Thirty-one participants completed the study. Most participants (97%) were men, white (94%) with a mean age of 68 years (range, 45–81). At baseline, systolic ejection fraction mean was 37.6% with a range of 10% to 65%. Most participants demonstrated a willingness to use the instruments for monitoring (range of adherence, 63–84 d [75%–100% of the study period], with a mean [SD] use rate of 79.9 [6.4] d). The participants with potential exacerbations rarely took action based on the data. The use of the instruments had no significant effect on self-management behaviors during the 3-month period. The participants reported that they found the instruments helpful and would recommend them to other patients with HF.

Conclusions: New strategies and instruments are needed to promote a patient-clinician partnership and actively engage patients in symptom monitoring and recognition. Easy-to-use and practical instruments for patients to monitor symptoms may lead to appropriate and accurate reporting as well as improved symptom management. Although the instruments used in this study resulted in symptom monitoring, appropriate action was not undertaken as a result of such monitoring.

Bonnie Wakefield, PhD, RN Investigator, VA Office of Rural Health, Veterans Rural Health Resource Center-Central Region, Iowa City VA Healthcare System, and The Comprehensive Access and Delivery Research and Evaluation Center at the Iowa City VA Healthcare System.

Patricia Groves, PhD, RN Assistant Professor, College of Nursing, University of Iowa.

Kariann Drwal, MS Health Science Specialists, VA Office of Rural Health, Veterans Rural Health Resource Center-Central Region, Iowa City VA Healthcare System, and The Comprehensive Access and Delivery Research and Evaluation (CADRE) Center at the Iowa City VA Healthcare System.

Melody Scherubel, BSN Health Science Specialists, VA Office of Rural Health, Veterans Rural Health Resource Center-Central Region, Iowa City VA Healthcare System, and The Comprehensive Access and Delivery Research and Evaluation Center at the Iowa City VA Healthcare System.

Peter Kaboli, MD, MS Professor, VA Office of Rural Health, Veterans Rural Health Resource Center-Central Region, Iowa City VA Healthcare System, Iowa City, IA, The Comprehensive Access and Delivery Research and Evaluation Center at the Iowa City VA Healthcare System, Iowa City, Iowa, and Division of General Internal Medicine, Department of Internal Medicine, University of Iowa Carver College of Medicine.

This study was supported by the Department of Veterans Affairs, Veterans Health Administration, Office of Rural Health, Veterans Rural Health Resource Center-Central Region, and the VA Health Services Research and Development Service through the Comprehensive Access and Delivery Research and Evaluation Center (HFP 04-149). The views expressed in this article are those of the authors and do not necessarily represent the views of the Department of Veterans Affairs.

The authors have no conflicts of interest to disclose.

Correspondence Bonnie Wakefield, PhD, RN, Iowa City VA Healthcare System, 601 Hwy 6 W, Mailstop 152, Iowa City, IA, 52246-2208 (bonnie.wakefield@va.gov).

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Background

Heart failure (HF) is a complex clinical syndrome that can be challenging for both patients and providers. For patients, management can be burdensome and the disease has a significant impact on health-related quality of life. For providers, medication management to control symptoms and prevent disease progression is complex and requires careful coordination of specialist and primary care. Thus, optimal management is dependent on a combination of appropriate medical care with patient participation and adherence to recommendations. The requirement of the nature of HF is that patients be engaged in self-care, including medication adherence, symptom recognition, and contacting the healthcare provider when appropriate1 to enable appropriate treatment adjustment to avoid decompensation. Failure to achieve clinical stability can be caused by patient’ s lack of knowledge2,32,3 and/or recognition of early warning signs of decompensation,4,54,5 nonadherence with therapeutic recommendations,6,76,7 and inadequate social or financial support.8–108–108–10

To maintain clinical stability, patients with HF must recognize often subtle but clinically significant symptoms such as dyspnea, fatigue, and volume overload that often precede decompensation. Weight increases anywhere from 7 to 30 days preceding admission are associated with hospitalization.11 Although it is believed that symptom recognition by patients and, when appropriate, contacting their healthcare provider could prevent exacerbations and subsequent hospital admission, current evidence indicates that patients often do not recognize symptoms and/or act on symptoms indicating HF-related decompensation. Symptom recognition is particularly problematic in older individuals.5,125,12 It was found in a recent review of symptom recognition that no prospective studies focused on patient’s ability to recognize and respond to symptoms in a home environment.13

With a lack of evidence-based, patient-centered instruments to facilitate symptom recognition and reporting, we hypothesized that an instrument that provides a visual display of monitoring data and data trends would improve symptom recognition, self-management, and confidence, thus enhancing between-visit communication between patients and providers. A graphical display of data was developed on the basis of the risk communication literature that recommends use of graphs over tabular forms14,1514,15 and reports improved patient understanding of risk with graphical presentation compared with verbal communication.16,1716,17 Compared with the tabular form, graphs can be used to attract attention, elicit better information extraction, and result in improved comprehension.18 Patients also prefer visual presentations14,1514,15 that are personalized,19 use color coding to enhance understanding,17 and use simpler displays.20 Improved ability to recognize key clinical changes is fundamental to improving patients’ clinical decision making. Thus, plotting values on a graph may provide a visual cue for patients who may not accurately perceive these symptoms and encourage them to contact their provider.

The instruments evaluated in this study are based on statistical process control charts, a method used to monitor performance by studying variation over time.21,2221,22 These charts are used to distinguish special cause variation, as opposed to normal or expected variation. For example, normal respiratory rate may vary between 12 and 24 breaths per minute; statistical process control charts are used to help identify when the rate is out of the expected range owing to a special cause variation such as volume overload. Similarly, weight may fluctuate daily but may be “out of control” with only a few pounds gain in a patient with HF.

The overall objective of this study was to evaluate the feasibility of 2 novel patient self-monitoring instruments designed to facilitate both HF symptom recognition and reporting of these symptoms to providers for timely treatment adjustments. A secondary goal was to examine what, if any, actions patients took when their symptoms indicated potential HF decompensation. Changes in self-care management before and after use of the instruments were evaluated, as were patients’ perceptions on the usefulness of the instruments in monitoring symptoms.

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Methods

Design

The study was approved by the University of Iowa Institutional Review Board and the Iowa City VA Medical Center Research and Development Committee. A pretest-posttest longitudinal design using questionnaires, patient recorded data, and interviews at a Midwestern Veterans Affairs Medical Center were used in this study. The study sample was composed of patients selected from a review of administrative databases who had either an inpatient admission for HF (DRG code 127) or an outpatient visit with International Classification of Diseases version 9 codes 402.01, 402.11, 402.91, 404.01, 404.03, 404.11, 404.13, 404.91, 404.93, and 428.0 through 428.9. Of those identified with these codes, the electronic medical record was reviewed to determine potential candidates who met the following inclusion criteria: (1) men and women aged 18 years or older, (2) diagnosis of chronic HF for at least 1 year or at least 1 HF-related hospitalization in the past 12 months, and (3) the ability to communicate in English. The exclusion criteria were as follows: (1) diagnosis of psychiatric conditions such as bipolar disorder, schizophrenia, psychosis; (2) mental retardation, organic mental disorder, dementia, or aphasia; (3) dependence on drugs or alcohol; or (4) cognitive impairment. Patients also had to have a working weighing scale at home.

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Monitoring Instruments Description

This study evaluated 2 monitoring instruments. The first was a weight chart in the form of a graph where patient’s baseline weight was entered (green zone), and 2 upper control limits were included to identify 2 and 5 lb greater than baseline weight (yellow and red zones, respectively; Figure 1). A modified Borg scale5,235,23 was used to evaluate patient dyspnea (Figure 2). No control limits were used for the Borg scale. Both figures show partial patient data to demonstrate how the instruments were completed by the patients.

FIGURE 1

FIGURE 1

FIGURE 2

FIGURE 2

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Measures

Demographic data were collected from the patient and included age, gender, race, marital status, and years of education. Clinical data were collected from the medical record and included left ventricular ejection fraction and number of comorbid conditions. Depression was measured using the Geriatric Depression Scale Short Form,24 which contains 15 statements assessing depressed mood. Respondents answer each question with a “yes” or “no” for how they have felt over the past week. Knowledge was measured using the Dutch HF Knowledge Scale, which is a 15-item questionnaire designed to assess general knowledge of HF, HF treatment, and symptom recognition.25 The scale differentiates patients with high and low HF knowledge; Cronbach’s α in a sample of 902 patients across 19 hospitals was .62.

At baseline, we interviewed patients about their HF self care. Questions were based on the Situation-Specific Theory of Heart Failure Self-Care,26 which addresses self-care processes in patients with HF, defined as self-care maintenance and self-care management. Self-care maintenance is a set of activities that promote physiologic stability and may include monitoring symptoms and adherence to recommended treatments. Self-care management encompasses symptom recognition and the decision-making responses to symptoms, including symptom evaluation, treatment, and evaluation of the effectiveness of the treatment. Self-care confidence underlies the relationship between self-care and outcomes. It is posited from this model that symptom recognition is crucial to treatment initiation.

Actions by patients in response to symptoms indicating potential HF decompensation were collected during weekly phone calls to the participants and by searching the electronic medical record for 3 months after study enrollment to collect data on the number and reasons for hospital admissions and number of emergency department visits. Self-care management was measured at baseline and 3 months with the Self-Care of HF Index (SCHFI),27 which contains 3 scales scored separately: self-care maintenance (choosing behaviors to maintain physiologic stability), self-care management (response to symptoms), and self-care confidence. The SCHFI has been shown to be valid and reliable.28 Each scale is scored using a Likert-type scale and standardized to a 100-point scale, with a change in a scale score of more than one half of a standard deviation considered clinically relevant. Patients’ perceptions on the usefulness of the instruments in monitoring their symptoms were evaluated using postintervention interviews.

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Data Collection

Databases were reviewed, and potential participants were identified. Patients received a letter in the mail preceding an upcoming outpatient clinic appointment and indicated their interest by returning a response form to the study coordinator. The potential participant was then telephoned to arrange a meeting with the study coordinator either immediately before or after the clinic visit. The study was explained, and the participants were encouraged to ask questions. Once consent was obtained, demographic and clinical data were collected and the participants completed the Geriatric Depression Scale, HF Knowledge, SCHFI instruments, and baseline interview.

The participants were then instructed in the use of the 2 monitoring instruments for weight and dyspnea (Borg scale). They were instructed to record weight and a Borg score daily for 3 months. The participants were instructed about the importance of weighing at the same time daily. We recommended that they weigh themselves first thing in the morning, after going to the restroom, before dressing, and before breakfast. The participants were also instructed about the importance of using the same scale and being dressed the same each time they weighed. For shortness of breath, they were instructed on the dyspnea scale ratings. The participants were encouraged to wait until the end of the day (for example, when taking evening medications) to rate shortness of breath for the entire day.

The study coordinator conducted weekly phone calls with the participants to answer patient questions and determine whether they contacted their provider about symptoms and, if so, what symptoms were reported. During the final contact phone call, the participant was interviewed to gather feedback on the use of the monitoring instruments to determine acceptability by and perceptions of the patients regarding the instruments. The participants received $25 for completing the study.

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Data Analysis

Data analysis was composed of descriptive statistics for all quantitative measures (means or frequencies). Adherence to weekly monitoring was analyzed using counts of the number of days data were entered for both weight and dyspnea. Data on the monitoring instruments were analyzed by visually inspecting each graph and identifying when and how often patients exceeded a 5-lb weight gain for 3 or more consecutive days. Weekly phone call data were then evaluated to determine what, if any, actions were taken by the patients when weight is in adherence with this parameter. We assessed symptom variability by calculating a mean and standard deviation of weight and dyspnea scores for each patient. Finally, the relationship between weight and Borg scores was assessed by calculating a Pearson r.

Baseline and 3-month scores for 2 of the 3 SCHFI scales (maintenance and confidence) were compared using paired t tests to assess for changes in self-care attributes in all patients. Baseline and 3-month scores were calculated for the third SCHFI scale, self-management, using paired t tests but only for patients who responded to the scale at each time (the management scale is scored only if the respondents indicate that they experienced dyspnea or ankle swelling).

Baseline and completion interviews were analyzed using basic qualitative descriptions, a method of qualitative content analysis that produces a “straight descriptive summary of the informational contents of the data organized in a way that best fits the data.”29(p. 338,339) For the baseline interview, a research assistant transcribed the structured interview for each patient and then grouped all responses together by each question. Thus, all responses to a particular topic were grouped together and differentiated using the assigned patient study identification number.

A coding framework was derived from the baseline interview guide, using the 5 stages from the theoretical model described earlier as categories (self-care maintenance activities, symptom recognition, symptom evaluation, self-care management activities, and treatment evaluation). Interview probes were used as the initial codes. Interview data were then coded independently by authors B.W. and P.G., who added codes for unexpected and unique responses as the analysis progressed. The 2 investigators met after coding the first 10 participants and, again, after coding all participants. In those meetings, they resolved any discrepancies in coding as well as renamed and collapsed codes as appropriate to the data. Consensus was reached on all codes and coding of data. Once data were coded, percentages were calculated by summing the number of participants with responses in each category divided by the total number of respondents.

Semistructured completion interview data were analyzed using the same method of qualitative description, with participant responses grouped according to interview questions. However, because more of these questions were open-ended (Table 1), more codes were derived during analysis rather than as part of the initial coding framework. Trustworthiness of the analysis was again achieved through the same double-coding and consensus methods.

TABLE 1

TABLE 1

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Results

Invitation letters were sent to 115 potential participants for a 3-month period. Thirty-four patients enrolled in the study; 2 dropped out, and 1 was lost to follow-up, resulting in 31 participants with complete data for analysis. Of the 31 participants, 97% were men and 94% were white; mean age was 68 years (range, 45–81 y) with a mean education of 12.7 years (range, 8–16 y). More than half (53%) were currently married. At baseline, systolic ejection fraction mean was 37.6% with a range of 10% to 65%; 11 participants had an ejection fraction at 30% or less. Length of time diagnosed with HF ranged from 1 to 13 years, with a mean (SD) of 5 years (3.2). Number of comorbidities ranged from 0 to 4 (mean, 2.5; mode, 3) and included hypertension (n = 27), diabetes/impaired fasting glucose (n = 22), chronic obstructive pulmonary disease/asthma (n = 15), and chronic kidney disease (n = 14). Baseline Geriatric Depression Scale mean (SD) was 4.1 (3.0) (range, 0–11) (Cronbach’s α, .82), indicating a low level of depressive symptoms in this group. Knowledge score mean was 11.4 (1.8) (range, 8–15) (Cronbach’s α, .45), indicating a moderate to good level of knowledge about HF.

Results from the baseline interview are presented in Table 2. Although most participants reported taking medication and limiting salt intake as ways to manage their HF, only half monitored their weight and fewer (30%) used some type of diary for monitoring; more than half reported dyspnea as a symptom, with half reporting swelling/fluid retention. The majority reported that having HF symptoms had resulted in a hospital stay in the past, and half reported that they had waited too long to call their physician when symptoms were present.

TABLE 2

TABLE 2

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Feasibility of the Instruments

The primary objective of the study was to examine the use of the instruments. Adherence to the monitoring instruments ranged from 63 to 84 days (75%–100% of the study period) with a mean (SD) use rate of 79.9 (6.4) days.

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Actions Taken by Patients in Response to Data

The secondary goal of the study was to examine what actions the participants took when their symptoms indicated potential HF decompensation. Calls made to providers and actions taken by the participants to address symptoms were determined during the weekly telephone calls. Visits to emergency department and hospitalizations were obtained from the electronic medical record. Eight patients (26%) experienced at least 1 episode of greater than 5-lb gain during 3 days or more (Table 3). In these 8 patients, during the 3-month monitoring period, none called their provider about HF symptoms. One was admitted for an HF exacerbation; he reported a 9-lb weight gain in 1 week to the study coordinator during the weekly call but had a scheduled clinic visit that day and was admitted. Very few patients took action on symptoms (see Patient-Reported Information in Table 3).

TABLE 3

TABLE 3

In the remaining patients, several occasionally experienced brief episodes of weight gain (1–2 lb) or dyspnea and most took actions such as resting, or limiting sodium, food, or fluid intake. Of these, 1 patient called their case manager to discuss dyspnea resulting in an emergency department visit. In addition to the 1 patient described in the previous paragraph, 1 patient was admitted for an HF exacerbation once during the study period with no prior provider calls or ED visits. One patient had 4 emergency department HF-related visits (preceded by 2 triage nurse contacts) and 2 hospitalizations for HF exacerbation (Table 4).

TABLE 4

TABLE 4

To assess variability in weight and dyspnea, means and standard deviations were calculated for each patient. These results are shown in Table 4, sorted from the highest to lowest standard deviations. Patients with greater weight variability were more likely to have ED and clinic visits and to be hospitalized for HF. Weight and dyspnea scores were significantly but moderately correlated (Pearson r = .37; P = .001).

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Changes in Self Care

Changes in overall self-care were evaluated before and after using the monitoring instruments. There were no significant differences in SCFHI scores during the 3-month period (Table 5). Although no significant changes were detected, the group had adequate self-care maintenance behaviors at baseline that improved slightly by 3 months. However, both management and self-care confidence decreased over time.

TABLE 5

TABLE 5

To further explore potential changes, we compared baseline and 3-month scores for each of the 10 questions in the self-care management scale and the 6 questions in the confidence scale. For self-care management, responses are scored on a 4-point Likert-type scale, where higher scores indicate greater frequency in performing the behavior. Two items improved significantly from baseline to 3 months: “How routinely do you weigh yourself?” (baseline, 3.03; 3 mo, 3.65; t = −3.45; P = .002) and “How routinely do you ask for low-salt items when eating out or visiting others?” (baseline, 1.71; 3 mo, 2.35; t = −3.23; P = .003). For the confidence scale, responses are scored on a 4-point Likert-type scale, where higher scores indicate greater confidence in performing the behavior. There were no significant differences in any of the individual items during the 3-month period. One item approached significance but actually diminished over time: “How confident are you that you can evaluate the importance of your symptoms?” (baseline, 3.17; 3 mo, 2.86; t = 1.88; P = .07).

We then compared the data from the baseline interview assessing self-management practices and the responses from the Maintenance scale of the SCHFI. The 3 items with the highest ratings on the maintenance scale were as follows: keep physician or nurse appointments (3.97), use a system (pill box, reminders) to help you remember your medicines (3.84), and try to avoid getting sick (eg, flu shot, avoid people with illness) (3.71). Although none of these were specifically identified by the patients in the baseline interview, the remaining items from the maintenance scale were consistent with the interview data.

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Patient Perceptions of the Instruments

Participant perceptions of the instruments were gathered through interviews at the completion of using the instruments for 3 months. Of the 31 participants, 71% (n = 22) expressed generally positive perceptions, stating that using the instruments helped to show when they were not doing well on a particular day, increased their awareness of their weight, and was helpful to identify trends. Negative perceptions were composed of the need to enter data on the instruments every day and some difficulty seeing the colors on the weight instruments.

When asked whether graphing symptoms improved their ability to monitor themselves, 60% (n = 19) responded yes, with 20% responding no (n = 7); the remaining were unsure or did not provide a response. The most common reason given for helpfulness was increasing their awareness of their weight and breathing patterns (n = 9; 30%), followed by the ability to look at patterns in the data (n = 5; 20%). When asked whether monitoring symptoms changed their HF management, most (n = 19; 60%) responded no, with 30% (n = 8) responding yes. Examples of changes were increasing activity/exercise (n = 3), improving diet (n = 3), and decreasing fluid intake (n = 1). Most thought the graphs provided useful information (n = 25; 80%) and helped to understand relationships between behavior and signs/symptoms (n = 9; 30%), track weight (n = 6; 20%), and increase in awareness of their condition (n = 7; 20%).

Most (n = 29; 90%) thought the graphs were easy to use, and 12 participants had no suggestions for improvement. Others suggested changes in the colors used (n = 6) or adding other parameters such as blood pressure, edema, stress, and pain (n = 9). On a scale of 1 to 5 (5 being very useful), 40% of the participants (n = 11) rated usefulness at 5; 11 rated it 3 or 4, with 2 participants rating the tracking as 1 or 2 (5 did not provide a rating). Nine (20%) noted that they planned to continue to use the graphs after the study, and most (n = 27; 87%) would recommend this type of monitoring and reporting instruments for other people with HF.

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DISCUSSION

In this study, patients demonstrated a willingness to use a paper-based instrument to monitor weight and dyspnea. Most found the instruments helpful and would recommend them to other patients with HF. However, those patients with potential exacerbations (ie, weight greater than 5 lb over baseline for 3 d or more) rarely took action based on the data. With the exception of weighing routinely and requesting low-salt items when eating away from home, use of the instruments had no significant effect on the overall self-management behaviors during the 3-month period. One item on the confidence scale of the SCHFI approached significance but actually diminished over time: how confident are you that you can evaluate the importance of your symptoms? It is possible the monitoring and weekly phone calls caused the participants to question their ability to evaluate symptoms; this finding requires further exploration.

This study tested an approach to improve patients’ recognition of symptoms that may need to be addressed, a necessary first step to treatment. A prior study evaluated the use of a weight and symptom diary. Although the study was a retrospective analysis, majority of those enrolled used the diary and had better outcomes than did the nondiary users.30 Thus, it seems that patients are willing and able to track symptoms but may need more intensive self-management support to take action based on the data.31

Self-monitoring is a consistently effective strategy to change health behaviors.32,3332,33 Patients with HF wait from an average of 3 days34 up to 2 weeks4 to report symptoms, and some patients wait up to 30 days to report weight gain.11 Past research has shown that patients ignore, do not perceive, or delay reporting symptoms indicating HF exacerbation, and they may not implement recommended self- management interventions to treat symptoms. Findings from this study are consistent with prior research that found that fluctuating symptoms may be more problematic than symptom severity is because patients may expect improvement on the basis of past fluctuations and, thus, do not seek care.35 Further work is needed to examine the association of fluctuating symptoms and subsequent resource use.

This study has a number of limitations. First, the sample was primarily male patients from 1 Midwestern Veterans Affairs Medical Center, limiting generalizability. Second, the monitoring instruments were paper-based that did not easily allow visualization of weight or dyspnea for more than a 1-week period or allow easy viewing of both weight and dyspnea on the same graph. Third, the participants were not systematically trained or given advice on when to contact their providers or what actions to take when their weight or dyspnea worsened. The participants were not formally tested for cognitive impairment, which is common in patients with HF.36,3736,37 Thus, it is likely that some mild cognitive impairment was present in this sample. The knowledge scale may have low reliability reflected by the Cronbach’s α in this study and in a prior study. Finally, the sample size was small and likely had inadequate power to detect changes in self-care.

The approach to self-monitoring described here needs to be tested in a larger more diverse population of patients with HF. Both instruments (weight and dyspnea) can be incorporated into a patient management Web site to allow simultaneous visualization of both weight and dyspnea for more than a 1-week period. Uploading to a patient Web site will also provide patient choice in use of either a technology approach or paper versions. Future evaluations of this approach will also include systematic training on when to contact their providers and actions to take when their weight or dyspnea exceeds control limits.

Optimal self-management of chronic illness involves engaging patients in their care and implementing strategies to help patients evaluate their symptoms and report them appropriately. Lack of monitoring and/or lack of recognition of gradually worsening symptoms means that exacerbations are not detected early, resulting in potentially preventable hospitalizations. In this study, patients reported the best adherence to medication taking and lowest adherence to symptom monitoring activities at baseline but were adherent to recording data on the monitoring instruments. However, few took action based when the recorded data indicated a potential exacerbation. New strategies and instruments are needed to promote a patient-clinician partnership and actively engage patients in symptom monitoring, recognition, and reporting. An easy-to-use and practical instrument for patients to monitor symptoms may lead to appropriate and accurate reporting and improved symptom management.

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What’s New and Important

  • Patients demonstrated a willingness to use a paper-based instrument to monitor weight and dyspnea, but those with potential exacerbations rarely took action based on the data.
  • Patients may need more intensive self-management support to take action based on the data.
  • New strategies and instruments are needed to promote patient-clinician partnerships and actively engage patients in symptom monitoring and recognition.
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Keywords:

heart failure; self management; symptom monitoring

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