مدل‌سازی بهينۀ رضایتمندی بیمار از پزشک مبتني بر روش¬هاي يادگیری ماشین
محورهای موضوعی : عمومى
- شادمهر
1
,
زینب الهدی حشمتی
2
,
فاطمه ثقفی
3
*
,
هادی ویسی
4
1 - .دانشگاه تهران
2 - استاد دانشگاه
3 - دانشیار دانشگاه تهران
4 - .
کلید واژه: ارتباط بیمار و پزشک, رضایتمندی, یادگیری ماشین, شبکه عصبی,
چکیده مقاله :
رويكرد بيمار محور در حوزه سلامت به تازگي در حوزه نظام پزشكي كشور ما مطرح شده است ولي تا كنون در زمينه عوامل رضايت بيمار از پزشك تحقيق علمي منتشر شده اي وجود ندارد. مقاله حاضر قصد دارد خلاء بيان شده را با ارزيابي علمي مبتني بر اطلاعات واقعي كسب شده از مطالعه ميداني پوشش دهد.در اين راستا با مرور ادبيات و مدلهاي حوزه ارائه خدمات؛ پرسشنامه اي براي حوزه سلامت طراحي و با نظر خبرگان مورد تاييد قرار گرفت. به منظور کسب نظر بیماران پرسشنامه بين 500 نفر از افرادی که عمل جراحی زیبایی بینی در تهران انجام دادند، توزيع شد و 395 پرسشنامه جمع آوري شد. تعداد براي تحليل داده ها، از سه روش درخت تصمیم، ماشین بردار پشتیبان و شبکه‌های عصبی، استفاده شد. تحليل نتايج بر حسب معيار صحت نشان داد كه کاراترین روش، در اولویت اهمیت عوامل موثر بر رضايت بيمار؛ روش شبکه عصبی بوده است. نتايج تحليل با اين روش حاكي از آن است كه موثرترین ویژگی در رضایتمندی بیمار از پزشک، اطلاعاتی است که بيمار انتظار دارد پزشک در اختیارش قرار دهد. نتايج رتبه بندي عوامل در مقايسه با ساير مطالعاتي كه تنها از روشهاي آماري براي تحليل استفاده شده بودنشان داد كه نتایج نسبتا مشابه بوده و یکدیگر را تایید می‌کردند. ولي توامنديهايي كه روش شبكه عصبي در مدلسازي دارد نقطه قوت اين روش نسبت به مطالعات مذكور است.
The patient-centered approach in the field of health has recently been proposed in the field of the medical system of our country, but until now there is no published scientific research on the factors of patient satisfaction with doctors. The present article aims to cover the stated gap with a scientific evaluation based on the real information obtained from the field study. A questionnaire was designed for the health sector and was approved by the opinion of experts. In order to get the opinions of patients, a questionnaire was distributed among 500 people who underwent rhinoplasty in Tehran, and 395 questionnaires were collected. Three methods of decision tree, support vector machine and neural networks were used for data analysis. The analysis of the results according to the accuracy criteria showed that the most efficient method, in priority, the importance of the factors affecting the patient's satisfaction; Neural network method. The results of the analysis with this method indicate that the most effective feature in the patient's satisfaction with the doctor is the information that the patient expects the doctor to provide. The results of ranking factors in comparison with other studies that only used statistical methods for analysis showed that the results were relatively similar and confirmed each other. But the strengths of the neural network method in modeling is the strength of this method compared to the mentioned studies.
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