مدلی برای بلوغ هوشمندی کسب‌وکار در حوزه مراقبت‌های سلامت بر پایه ترکیب روش‌های دلفی و dematel anp

بلوغ هوشمندی کسب‌وکار که هدف اصلی این پژوهش است، نقش مهمی در تصمیم‌گیری، برنامه‌ریزی، کنترل و نظارت هوشمند در حوزه مراقبت‌های سلامت دارد. بصورت کلی، به منظور شناسایی عوامل موثر از روش دلفی و تجمیع نظرات خبرگان استفاده گردید و به منظور تاثیرگذاری و تاثیرپذیری شاخص‌ها و در نهایت اولویت‌بندی آن‌ها از ترکیب روش دیمتل و فرآیند تحلیل شبکه بهره گرفته شد. نمونه آماری شامل 20 نفر از خبرگان هدفمند دانشگاهی و کارشناسان حوزه مراقب‌های سلامت هستند. گردآوری داده‌ها در هر دو بخش از طریق پرسشنامه صورت پذیرفت. طبق نتایج بخش دلفی، 26 شاخص اصلی نهایی شده در تحقیق، شناسایی شد که در سه دسته اصلی شامل معیارهای سازمانی، فرآیندی و فناوری تقسیم بندی می‌شوند. طبق نتایج بخش دیمتل و فرآیند تحلیل شبکه به‌ترتیب معیارهای زیرساخت فنی انعطاف‌پذیر و قابل توسعه (سخت‌افزاری و نرم‌افزاری)، کیفیت داده و سیستم و تعریف درست از مشکلات و فرایندهای هوشمندی کسب‌وکار به‌عنوان سه معیار با رتبه برتر در بلوغ هوشمندی کسب‌وکار اولویت‌دهی شدند. مدل بلوغ هوشمندی کسب‌وکار پیشنهادی پژوهش، می‌تواند نقشه راهی برای پیاده‌سازی موفق بلوغ هوشمندی کسب‌وکار در حوزه مراقبت‌های سلامت باشد.

a business intelligence maturity model in healthcare based on the combination of delphi and dematel anp methods

the maturity of business intelligence, which is the main goal of this research, plays an important role in intelligent decision making, planning, control and monitoring in the field of health care. in order to identify the effective factors, the delphi method was used and experts' opinions were, and in order to determine the effectiveness and effectiveness of the indicators and finally to prioritize them, used the danp method. the statistical sample includes 20 targeted academic experts and health care experts. according to the results of the delphi section, 26 main indicators finalized in the research were identified, which are divided into three main categories including organizational, process and judgment criteria. according to the results of the danp process, flexible and expandable technical infrastructure criteria, data and system quality and the correct definition of business intelligence problems and processes were prioritized as the three criteria with the highest ranking in the maturity of business intelligence. the business intelligence maturity model proposed by the research can be a road map for the successful implementation of business intelligence in the field of health care.1. introductionbusiness intelligence is one of the most important issues in recent decades as a decision making system for managers of organizations in order to plan, control and intelligently monitor companies and their subordinate units and measure the achievement of organizational goals. business intelligence includes a comprehensive set of tools, technologies and products designed to collect, aggregate, analyze and present usable data (reinschmidt j. & francoise a., 2000) introduction of new and complex medical technologies, the global trend of increasing length longevity, the unexpected development of chronic diseases and emerging diseases (such as covid 19) can lead to an increase in health care costs to unsustainable levels (janssen & moors, 2013; qaseem et al., 2012). public or private medical care organizations have focused their efforts on achieving new, cost effective and efficient levels of care (romanow et al., 2012). for this purpose, information technologies play a fundamental role by transforming data into knowledge that can improve patient care, medical care facilities, and process management (behkami & u. daim, 2012; li & mao, 2015; pai & huang, 2011). considering the very important role of data in supporting the improvement of the organizational level, business intelligence is one of the important areas of research for researchers and activists in the treated field (chen et al., 2012).the field of business intelligence has improved significantly over the past decade and has promising applications in the health field (el gayar & timsina, 2014; gandomi & haider, 2015). indeed, business intelligence can not only improve outcomes in healthcare organizations but also help them achieve continuous improvement and precision in medicine (christensen et al., 2008; gastaldi et al., 2015; tremblay et al., 2012).investigating the process of information production and transmission in the field of healthcare is of great importance. today, organizations active in this field need correct information at the right time, in order to make the best decision by the right person. but many of the systems used by users do not have appropriate and expected