The impact of a primary care e-communication intervention on the participation of chronic disease patients who had not reached guideline suggested treatment goals

Lussier, Marie-Thérèse; Richard, Claude; Glaser, Emma; Roberge, Denis

doi:10.1016/j.pec.2015.11.007

Cited by 24 publications

(30 citation statements)

References 36 publications

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“…A description of the randomization process for the original sample is reported in the primary paper . Figure describes the consort flow of patients.…”

Section: Resultsmentioning

confidence: 99%

“…Audio‐taped encounters were coded with the Roter Interaction Analysis System (RIAS) and MEDICODE . These two validated coding systems and the following measures are described in detail in Lussier et al . RIAS ascribes an interaction code to all utterances spoken by the physician and the patient during an entire encounter.…”

Section: Methodsmentioning

confidence: 99%

“…The sample size used here was based on participants from a randomized control trial (n=221) . Analyses concerning medication information are based on a subset of the sample that had complete medication recall data (n=159).…”

Section: Methodsmentioning

confidence: 99%

“…This study is an observational study within a randomized control trial. Results from the randomized control trial concerning communication have been reported elsewhere …”

Section: Introductionmentioning

confidence: 99%

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Communication and patient participation influencing patient recall of treatment discussions

Richard

Glaser

Lussier

2016

Health Expectations

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126

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ContextPatient recall of treatment information is a key variable towards chronic disease (CD) management. It is unclear what communication and patient participation characteristics predict recall.ObjectivesTo assess what aspects of doctor‐patient communication predict patient recall of medication information. To describe lifestyle treatment recall, in CD primary care patients.DesignObservational study within a RCT.Setting & participantsCommunity‐based primary care (PC) practices. Family physicians (n=18): practicing >5 years, with a CD patient caseload. Patients (n=159): >40 years old, English speaking, computer literate, off‐target hypertension, type II diabetes and/or dyslipidaemia.Main variablesPatient characteristics: age, education, number of CDs. Information characteristics: length of encounter, medication status, medication class. Communication variables: socio‐emotional utterances, physician dominance and communication control scores and PACE (ask, check and express) utterances, measured by RIAS. Number of medication themes, dialogue and initiative measured by MEDICODE.Main outcome measuresRecall of CD, lifestyle treatment and medication information.ResultsFrequency of lifestyle discussions varied by topic. Patients recalled 43% (alcohol), 52% (diet) to 70% (exercise) of discussions. Two and a half of six possible medication themes were broached per medication discussion. Less than one was recalled. Discussing more themes, greater dialogue and patient initiative were significant predictors of improved medication information recall.DiscussionCritical treatment information is infrequently exchanged. Active patient engagement and explicit conversations about medications are associated with improved treatment information recall in off‐target CD patients followed in PC.ConclusionProviders cannot take for granted that long‐term off‐target CD patients recall information. They need to encourage patient participation to improve recall of treatment information.

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“…A description of the randomization process for the original sample is reported in the primary paper . Figure describes the consort flow of patients.…”

Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

“…This study is an observational study within a randomized control trial. Results from the randomized control trial concerning communication have been reported elsewhere …”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Communication and patient participation influencing patient recall of treatment discussions

Richard

Glaser

Lussier

2016

Health Expectations

Self Cite

126

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“…An essential aspect to ensure full adherence to the treatment is the assessment of transplant recipient needs and his/her expectations while establishing a good therapeutic alliance[9]. Many studies evaluating the relationship between the healthcare team and the patient highlighted the need for a relationship based on trust and clarity for the sharing of information regarding the treatment course[10,11]. Even psychological and psychosocial aspects can alter the response to treatment[12,13]: Mood disorders, high levels of anxiety, hostility, and the presence of “unstable” personality traits are associated with an increased risk of non-adherence to medical prescriptions in kidney transplant recipients[14-16].…”

Section: Introductionmentioning

confidence: 99%

Psychological perspective of medication adherence in transplantation

Pasquale

Veroux

Fornaro

et al. 2016

WJT

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AIMTo identify the risk factors and the post-transplant psychological symptoms that affect adherence to therapy in a population of kidney transplant recipients.METHODSThe study examined the psychological variables likely responsible for the non-adherent behavior using a psychological-psychiatric assessment, evaluation of the perception of patients’ health status, and an interview regarding the anti-rejection drug therapy assumption. The study included 74 kidney transplant recipients.RESULTSIndividuals with a higher level of education and more years since transplantation showed better mental balance. Regarding gender, women appeared to be less adherent to therapy. Further, the years since transplantation adversely affected the proper pharmacological assumption. Adherence to therapy did not significantly change with the mental health index.CONCLUSIONThe biopsychosocial illness model provides a conceptual frame of reference in which biological, psychological, and social aspects take on the same importance in the adherence to treatment protocols. For effective management, it is necessary to understand the patients’ personal experiences, their assumptions about the disease, health status perception, and mood, and to identify any “barriers” that could cause them to become noncompliant.

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Effect of Smartphone-Enabled Health Monitoring Devices vs Regular Follow-up on Blood Pressure Control Among Patients After Myocardial Infarction

et al. 2020

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IMPORTANCESmart technology via smartphone-compatible devices might improve blood pressure (BP) regulation in patients after myocardial infarction. OBJECTIVES To investigate whether smart technology in clinical practice can improve BP regulation and to evaluate the feasibility of such an intervention. DESIGN, SETTING, AND PARTICIPANTS This study was an investigator-initiated, single-center, nonblinded, feasibility, randomized clinical trial conducted at the Department of Cardiology of the Leiden University Medical Center between May 2016 and December 2018. Two hundred patients, who were admitted with either ST-segment elevation myocardial infarction or non-ST-segment acute coronary syndrome, were randomized in a 1:1 fashion between follow-up groups using smart technology and regular care. Statistical analysis was performed from January 2019 to March 2019. INTERVENTIONSFor patients randomized to regular care, 4 physical outpatient clinic visits were scheduled in the year following the initial event. In the intervention group, patients were given 4 smartphone-compatible devices (weight scale, BP monitor, rhythm monitor, and step counter). In addition, 2 in-person outpatient clinic visits were replaced by electronic visits. MAIN OUTCOMES AND MEASURESThe primary outcome was BP control. Secondary outcomes, as a parameter of feasibility, included patient satisfaction (general questionnaire and smart technology-specific questionnaire), measurement adherence, all-cause mortality, and hospitalizations for nonfatal adverse cardiac events. RESULTSIn total, 200 patients (median age, 59.7 years [interquartile range, 52.9-65.6 years]; 156 men [78%]) were included, of whom 100 were randomized to the intervention group and 100 to the control group. After 1 year, 79% of patients in the intervention group had controlled BP vs 76% of patients in the control group (P = .64). General satisfaction with care was the same between groups (mean [SD] scores, 82.6 [14.1] vs 82.0 [15.1]; P = .88). The all-cause mortality rate was 2% in both groups (P > .99). A total of 20 hospitalizations for nonfatal adverse cardiac events occurred (8 in the intervention group and 12 in the control group). Of all patients, 32% sent in measurements each week, with 63% sending data for more than 80% of the weeks they participated in the trial. In the intervention group only, 90.3% of patients were satisfied with the smart technology intervention. CONCLUSIONS AND RELEVANCEThese findings suggest that smart technology yields similar percentages of patients with regulated BP compared with the standard of care. Such an intervention (continued)

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The impact of a primary care e-communication intervention on the participation of chronic disease patients who had not reached guideline suggested treatment goals

Cited by 24 publications

References 36 publications

Communication and patient participation influencing patient recall of treatment discussions

Communication and patient participation influencing patient recall of treatment discussions

Psychological perspective of medication adherence in transplantation

Effect of Smartphone-Enabled Health Monitoring Devices vs Regular Follow-up on Blood Pressure Control Among Patients After Myocardial Infarction

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