Development of an evidence- and narrative-based patient decision aid for secondary prevention of myocardial infarction

ID: 

3136

Session: 

Poster session 3 Friday: Evidence Tools / Evidence synthesis - creation, publication and updating in the digital age

Date: 

Friday 15 September 2017 - 12:30 to 14:00

Location: 

All authors in correct order:

Mu W1, Zhai JB2, Shang HC3, Huang YH1, Li J1, Li YF1, Wang RH1, Wang BH1
1 The 2nd Affiliated Hospital of Tianjin University of Traditional Chinese Medicine, China
2 Tianjin University of Traditional Chinese Medicine, China
3 Key Laboratory of Chinese Internal Medicine of Ministry of Education and Beijing, Dongzhimen Hospital, Beijing University of Chinese Medicine, China
Presenting author and contact person

Presenting author:

Wei Mu

Contact person:

Abstract text
Background: Cardiovascular diseases (CVDs) are the top causes of death worldwide. In China, CVDs affected 29 million patients in 2013, 2.5 million of whom had prior myocardial infarction. Prevention is the best treatment for myocardial infarction. With a variety of pharmaceutical interventions at hand, consumers urgently need a tool to assist them in the decision-making process.
Objectives: A patient decision aid (PDA) comparing preventative treatments for myocardial infarction is developed using methods and techniques of evidence-based and narrative-based Medicine, to fill the gaps in the implementation of these interventions in primary healthcare.
Methods: The PDA contains primarily statistical evidence from synthesis of quantitative study and narrative evidence from synthesis of qualitative study. Steps to generate statistical evidence include: 1) make a list of commonly used drugs for infarction prevention through systematic search; 2) collect original data of pre- and post-market clinical research from open and grey sources; 3) conduct network meta-analysis to compare multiple interventions on outcomes such as efficacy, safety, economics and acceptability; 4) transform statistics into easily comprehensible evidence; and, 5) evaluate the evidence using GRADE Profiler. Steps to generate narrative evidence include: 1) plan in-depth interviews with target consumers; 2) collect stories of searching for medical solutions regarding infarction prevention; 3) analyze and synthesise texts using Altas.ti; and, 4) transform stories into narrative evidence.

Innovative features: Comparisons between single drugs (such as statins) with drug combinations (such as statins and blood-invigorating and qi-tonifying Chinese patent drugs) and comparisons between combined use of western drugs with combined use of western drugs and traditional Chinese patent drugs will be made, to fit in the real-world situation. Narrative evidence may provide psychological support for those in need.

Conclusions: The PDA could be an effective evidence tool to implement preventative measures for myocardial infarction and facilitate shared decision making at the primary care level.