Böbrek dağıtım sistemi için yeni bir karar destek modeli
A new decision support model for kidney allocation system
Yazar: EMRE METERELLİYOZ
Danışman: YRD. DOÇ. DR. ÖZGÜR KABAK
İstanbul Teknik Üniversitesi / Fen Bilimleri Enstitüsü / Endüstri Mühendisliği Ana Bilim Dalı
Derece: Yüksek Lisans, 2015
Konu: Endüstri ve Endüstri Mühendisliği = Industrial and Industrial Engineering
Dizin: Lojistik regresyon analizi = Logistic regression analysis ; Lojistik regresyon modelleri = Logistic regression models ; Test istatistikleri = Test statistics ; Çok değişkenli istatistik = Multivariate statistic ; Çok kriterli karar verme = Multi criteria decision making

Özet:
Organ nakli son seviye organ yetmezliğe girmiş hastalar için hayat kurtaran, yaşam kalitesini artıran kalıcı bir tedavi yöntemidir. Hastalara kalıcı bir çözüm sunmasına rağmen kısıtları çok olan ve kompleks bir tedavidir. Bu kısıtlardan en önemlisi, sistemdeki arz ve talebin dengesizliğidir. Nakle uygun sağlıklı organ kaynağı sayısı çok az iken nakil bekleyen hasta sayısı gün geçtikçe artmaktadır. Arz edilen organın hangi hastaya verileceği kararı çözülmesi gereken en önemli problemdir. Bu problemi yönetebilmek için iyi planlanmış bir organ dağıtım sisteminin kurgulanması gerekmektedir. Literatürde organ dağıtım sistemleri genel olarak iki ana amaç üzerine yoğunlaşmaktadır. Bunlardan ilki nakil başarısını sağlamak, ikincisi ise hastalar arası hakkaniyeti gözetmektir. Bu iki amaç doğrultusunda en uygun hastanın seçilmesi kararı karar verme problemi olarak karşımıza çıkmaktadır. Nakil operasyonunun kompleks ve aşamalı yapısı, başarıyı ve hakkaniyeti etkileyen faktörlerin çokluğu ve değişkenliği süreci çok kriterli bir karar verme problemine dönüştürmektedir. Bu çalışmada en çok nakil yapılan organ olan böbreğin dağıtımı problemi ele alınmıştır. Donör organ bazında en uygun hastanın belirlenmesi için Türkiye'de 2008-2014 arasındaki gerçekleştirilen nakillerin verileri detaylı bir şekilde incelenmiştir. Bu inceleme sonucunda, yeni bir böbrek dağıtım sistemi tasarlanmasının gerekliliği görülmüştür. Bu yeni sistemin amacı, donör böbreklerin en verimli şekilde uygun alıcılarla eşleştirilmesidir. Buradaki verimlilikten kasıt nakil başarısının artışını hedeflerken aynı zamanda hakkaniyeti de değerlendirerek uygun hasta-donör eşleştirmesinin yapılmasıdır. Bu amaç doğrultusunda mevcut sistemin verileri ve literatür bilgisi kullanılarak başarıya ve hakkaniyete etki eden değişkenler tespit edilip her birinin ağırlıkları belirlenmiştir. Bu çalışmanın özgün yanı mevcut ulusal organ dağıtım sisteminin süreçlerini detaylı incelenip akış şemalarının ortaya konulması,  sistemdeki verilerin detaylı sayısal analizlerinin yapılması ve bu analizlerin önerilen karar destek modeli için girdi olarak kullanılmasıdır. Yapılan analizler neticesinde bir böbrek dağıtım sistemi için önemli olan kriterler belirlenmiş ve belirlenen tüm kriterler hakkaniyet ve başarı başlıkları altında toplanmıştır.  Çalışma sonucunda hakkaniyet ve başarı faktörlerini dengeleyerek, donör böbrek çıktığında en uygun hastayı seçen yeni bir karar destek modeli önerilmiştir.

Abstract:
Organ transplantation is a vital role in treatment of the end-stage organ failure patients. Transplantation improves quality of life and life expectancy in most cases. Developing techniques in medical surgery and increasing of the usage of immunosuppressive agents make the transplantation operation safer year by year. Due to that, it becomes routine treatment choice for most of patients who are fighting with end-stage organ failure.
Among the others, kidney is the most transplanted organs. The reason behind the this statistic is that most of the other organs like liver, heart and lungs have vital role in continuation of life and there is no alternative treatment for end-stage failure  of these organs. Because of the fact that, most people are died while waiting the new organ. This causes the limitation of the transplantation of these organs at first. Different from those, end-stage kidney failure patients have more chance to continuation of life than the others, even though they do not receive new organ. Dialyses treatment is an alternative treatment for end-stage kidney failure patients. By receiving dialysis treatment, a patient continues his/her life over the years. However, it is only ancillary treatment. While the transplantation improves quality of life, dialysis treatment is not improve life expectancy and quality. Dialyses treatment has many side effects. Patients who receive dialyses treatment get worse and decay slowly over the years in many cases because the dialyses treatment affects entire body badly. Despite all, dialyses treatment is a jackpot for the end-stage kidney failure patients. It allows continuing the patient life over the years. In other words, patients can wait the transplantation time without kidney over the years and it directly affects the number of the transplantation statistics. 
In kidney transplantation, Continuation of patient life over the years by receiving ancillary treatment causes other problem. The main problem is that patients who wait the organ transplantation treatment in the ordered list are increasing day by day. Besides, scarce of suitable deceased (cadaver) donors makes the problem more severe. These two situations make the gap between recipient and donor bigger day by day. The well-modeled organ allocation system is required to manage this kind of imbalance between the donors and recipients. Decision makers and policy makers should overcome these imbalances by both designing allocation systems and making policies that increase the organ donations and number of donors.
When developing organ allocation systems, decision makers should consider many different criteria and define the objective clearly according to the policies, human rights and medical/ethics considerations. In the literature, there are two common terms, called as utility and equity, which are defined as objectives of the organ allocation systems. While the utility term mostly refers the medical benefits, equity refers the justice among the recipients. Utility or medical benefit means the donor organ should use for a patient who lives for many years with the donor kidney as a part of his/her body. Equity can be explained as "first in first out" principle or give priority to special cases such as pediatric, zero-HLA mismatch or elder patients, etc.  
In the literature and most of the organ sharing systems, allocation criteria are evaluated under these two terms. There are many different applications to balance the tradeoff between the equity and utility. Decision makers are using the utility and equity criteria in different ratios/priorities according to their policies. For instance, Singapore and South Korea give priorities the patients who made organ donation before falling organ failure. Another example is special wait list for elder patients that accept only elder donors. In this way, elder patients both receive the organ promptly and do not inconvenience the younger patients. The system that performs the equity principle largely while increasing medical utility is applied in both United State and European Union.
In this study, it is focused on allocation process of kidney transplantation because of its structure and constraints. Kidney allocation process is a complex problem with its conflicting criteria and multiple alternatives. Confliction occurs mostly in criteria, which can be evaluated under the both utility and equity. Due to that, kidney allocation problem is defined as multi criteria decision-making problem. In the literature, decision-making methods are mostly applied in healthcare for following areas: medical diagnosis processes, patient participation, selection of treatment method, evaluation of healthcare service, etc. 
It is focused on the national kidney allocation system of Turkey, in this study. The system was put into practice in 2008 by the laws and regulations. The national system centralizes the all of transplantation process, hierarchically -national, regional and transplantation center levels. Before 2008, there are lots of transplantation center and each of them manage their own processes. Patients can be enrolled each center's waiting list separately. With the national system, these type of inefficiencies are blocked. Overall transplantation process has become centralized and easily manageable structure. 
Firstly, the national kidney transplantation processes are analyzed from end to end. For each step, detailed process flows are revealed. It is one of the novel parts of this study. By this study, processes of donor acceptance, organ removal, organ distribution (in emergency cases, in zero-HLA mismatch, in normal situation) are constituted briefly. The existing system is explained in detailed and process flows diagrams are generated according to both laws and regulations that regulate the system and experts opinions that represent experience and knowledge of system.
Secondly, data, which cover the kidney transplantations in the existing system in Turkey between 2008 and 2014, are analyzed in details. Data analysis is also one of the novel parts of this study. Waiting list patients, donors and transplantation data are analyzed separately. According to the descriptive statistic, there are 22,000 patients in the waiting list at the end of October-2014. %2 of these patients is re-enrolled after one or more transplantations. The mean age of waiting list patients is 50. A patient receives dialysis during 78 months on average before transplantation. These statistics shows that there is imbalance between supply and demand. It is undeniable fact that receiving dialysis treatment more than 24 months reduces the transplantation success rate in the literature. Seven patients in every 100 patients died while waiting healthy kidney. Istanbul region has the highest number of patients in waiting list. Beside these statistics, Izmir region is the first and Istanbul is the second region in terms of deceased donor number. 
According to the transplantation statistic, there are 12,235 transplantation operation between 2008 and 2014. In a quartile of transplantations, source of donor is cadaver. In this study, only transplantations which kidney is removed in cadaver donor are taken into account. Operations that transplant from live donors will cause the serious health impairments for live donor source. Due to that, number of organ donation and cadaver donor should be increased by policies. A transplanted patient is 39 years old in average and cadaver donor is 40 years old in average. The age gap between the transplanted patient and donor is 16. It can be tell that transplantation operations are performed between the same age group donor-recipients pair. Ischemia time that is defined as time between the graft removal and transplantation is 16 hours in transplantations given period. Concordantly, %71 of operations is performed within the same region. 
Thirdly, success rate of the national kidney allocation system is calculated. To calculate the success rate, time period is chosen and some assumptions are set. The success rate is calculated for one-year period that defined as following year after transplantation. Assumptions are related to failure situation. When it is labeled the operation as "success/failure" within the following first year, "rejection, re-enrollment, receiving re-dialysis and died" situations are checked and if one of them is satisfied then operation is labeled as failure. With the rate of %84, one-year success rate of the existing system is poor when it is compared the other systems such as UNOS (United Nations Organ Sharing) and ET (Euro Transplant). 
To increase the success rate, the new kidney allocation system should be designed. In the new kidney allocation system, criteria should be determined in respect to both medical utility and equity. At first, criteria related to success/failure of transplantation are determined by using statistical analysis such as t-test, chi-square tests, etc. Criteria that have significant effect on transplantation are dialysis time, previous transplantation history, patient age/age group, patient BMI (Body Mass Index), donor age/age group, donor unblock decision, patient-donor age group compatibility, patient-donor HLA compatibility, ischemia time and ratio of donor BSA (Body Surface Area) and Patient BSA. These success related criteria are grouped as patient related, donor related and transplant related. These three group represent the utility factor. Beside these criteria, patient waiting time and patient pediatric situation are determined under the equity factor. After criteria are determined, decision hierarchy is generated and weight of each criteria is determined by using both expert opinions and statistical inferences. At the top of decision hierarchy, suitable candidate is chosen among the alternative patients by using utility and equity scores for a new donor kidney. At the breakdown of hierarchy, utility and equity scores are calculated. Success rates are calculated by using logistic regression models for three criteria group separately at the breakdown of utility. Combination of the result of the logistic regressions constitutes the utility score. Equity scores calculated as combination of the patient waiting time and patient pediatric situation criteria. After the calculation of utility score (combination of donor related, patient realted and transplantation related success rates) and equity score for each donor-patient pair, global scores are calculated. Best candidate patient who has the highest global score is selected for transplantation.
At last, in this study, a novel decision support system for kidney allocation process that considers both equity and utility factors is proposed.