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Practice & Opinion of Doctors in Hospitals toward Referral System in Iraq
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Background: Primary Health care (PHC) is unanimous to be the cornerstone of a person-centered health system. While the adoption of a well-function, two-way, and organized referral system is the mainstay in the development of an efficient healthcare delivery system.  

Objective: To Assess the practice & opinion of doctors in the hospitals toward the referral system.  to determine the doctors in the hospital's commitment to referral system instructions and guidelines.

Subjects and Methods: A cross-sectional study with analytic elements was conducted in nine Iraqi governorates. Eight doctors from each health directorate, resulting in a total of 72 doctors using a specially designed questionnaire. Statistical analysis was done by using SPSS, the P≤0.05 was considered statistically significant.

Results: of the total 72 physicians, 31(43.1%) aged 40-49years, 48(66.7%) were males, and 58(80.6%) were specialists., 58 doctors (80.6%) had no coordination with the PHC-doctors, the same percentage considered the current referral system is ineffective. PHC patients-crowded, doctors-shortage were the causes of inadequately filling PHC-part of the referral form. And PHC-hospital doctors-coordination had a significant association with their age, gender, and their thinking about adequate filling.

Conclusion: despite the importance of the referral system, half of the doctors disagreed about the current referral system’s effectiveness; & most of them had no coordination with the PHC-doctors. PHC crowded/doctors’ shortage the main causes of inadequate filling PHC part of referral-form.

 

 

 

الملخص:

الخلفية: تعتبر الرعاية الصحية الأولية بالإجماع حجر الزاوية في نظام صحي يركز على المريض. في حين أن اعتماد نظام إحالة جيد ثنائي الاتجاه ومنظم هو الدعامة الأساسية في تطوير نظام فعال لتقديم الرعاية الصحية.

الهدف: تقييم ممارسة ورأي الأطباء في المستشفيات تجاه نظام الإحالة. كذلك لتحديد مدى التزام الأطباء في المستشفى بتعليمات وإرشادات نظام الإحالة.

طريقة البحث: أجريت دراسة مقطعية مع عناصر تحليلية في تسع محافظات عراقية. ثمانية أطباء من كل مديرية صحية ، مما أدى إلى ااشتراك 72 طبيبًا في استبيان مصمم خصيصًا للبحث. تم إجراء التحليل الإحصائي باستخدام SPSS ، واعتبر P≤0.05 ذو دلالة إحصائية.

النتائج: من إجمالي 72 طبيبًا ، 31 (43.1٪) تتراوح أعمارهم بين 40-49 عامًا ، 48 (66.7٪) من الذكورو 58 (80.6٪) من المتخصصين. ، 58 (80.6٪) منهم ليس لديهم اي تنسيق مع أطباء الرعاية الصحية الأولية. و بنفس النسبة يعتبرون نظام الإحالة الحالي غير فعال. ازدحام المرضى في المراكز ونقص الأطباء هي اهم أسباب نقص ملأ نموذج الإحالة الخاص باطباءالمراكز الصحية بشكل مناسب. وكان لتنسيق أطباء مستشفى الرعاية الصحية الأولية علاقة كبيرة مع العمر والجنس وتفكيرهم في الملأ االنموذجي.

الخلاصة: بالرغم من أهمية نظام الإحالة ، اختلف نصف الأطباء حول فعالية نظام الإحالة الحالي. ومعظمهم ليس لديهم اي تنسيق مع أطباء المراكز الصحية. ازدحام الرعاية الصحية الأولية / نقص الأطباء اهم الأسباب الرئيسية لضعف ملأ نموذج الإحالة.

 

 

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Publication Date
Mon Nov 01 2010
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Characterization of Quartz and Calcite Particle size Presents in Local Dust Fell on Baghdad on June 2009
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Mon Dec 23 2019
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Fri Jan 01 2021
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Deposited Cu (In, Ga) Se2 (CIGS) by spin-coating technique as an absorber layer of solar-cells
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Sun Jan 01 2017
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Standard levels for measuring the administrative work of sport unions in the Iraqi national union Olympic Committee
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Designing Primers with a Plant Signal Peptide to Enhance the Expression of GBA1 in Transgenic Soybean Plants
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Evaluation of Machine Learning Techniques for Missing Well Log Data in Buzurgan Oil Field: A Case Study
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The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti

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