Performans yönetim sistemi ve veri zarflama analizi'nin sağlık sektöründe uygulanması
Performance management systems and application of data envelopment analysis in healt care organizations
- Tez No: 39881
- Danışmanlar: DOÇ.DR. FÜSUN ÜLENGİN
- Tez Türü: Yüksek Lisans
- Konular: Endüstri ve Endüstri Mühendisliği, Industrial and Industrial Engineering
- Anahtar Kelimeler: Belirtilmemiş.
- Yıl: 1994
- Dil: Türkçe
- Üniversite: İstanbul Teknik Üniversitesi
- Enstitü: Fen Bilimleri Enstitüsü
- Ana Bilim Dalı: Belirtilmemiş.
- Bilim Dalı: Belirtilmemiş.
- Sayfa Sayısı: 149
Özet
ÖZET Ekonomik büyüme ve kalkınmanın temel hedefi olan performansın arttırıl ması; her organizasyonun, performans yönetim sistemini benimsemesini zorunlu hale getirmiştir. Performans yönetimi anlayışında, işletme performansı işletmeyi oluşturan sistemin tüm bileşenlerinin etkileşimini toplam sonuç olarak vereceği için, çağdaş işletme anlayışının egemen olduğu her işletmede değişik model ve tekniklerle performans ölçümüne ilişkin uygulamalar görülmektedir. Ekonomik ve sosyal gelişme çabası içinde olan ülkemizde sağlık sektörünü çağdaş işletmecilik anlayışından ayrı tutmak imkansızdır. Türkiye'deki mevcut hastanelerin bugünkü yetersizlikleri, türlü sosyal politik ve ekonomik nedenlere bağlıdır. Ancak, hastanelerimizin bugünkü yetersiz durumlarının yalmzca sayılan nedenlere bağlı kalınarak açıklanması yanlış olacaktır. Bununla birlikte, hastane lerin modern işletmecilik anlayışıyla yönetilmemel eri, onların toplumun gereksin melerini yeterince karşılamaktan uzak kalmalarının en önemli nedenlerinden birisidir. Karmaşık bir kurum olarak değerlendirilen hastanelerin yönetiminde sorun ların yaşanmaması ve faaliyetlerin sistemli biçimde yürütülebilmesi için, yöne ticinin, üretim girdileri (hastalar, insangücü, malzeme, fiziksel ve parasal kaynak lar) ile çıktıları (hasta ve yaralıların tedavisi, personelin hizmet içi eğitimi, araş tırma geliştirme faaliyetleri, toplumun sağlık seviyesinin yükseltilmesi) arasında ki dengeyi çok iyi kurabilmesi gerekir. Hastanenin fonksiyonları için saptanan hedeflerinin ne derecede gerçekleşti rildiğinin belirlenmesi, gerçekleştirilememesi halinde bunların nedenlerinin araştı rılması, hastane içinde ve dışında bilgi akışını sağlayacak bilgi sisteminin kurul ması için etkin ve güvenli ölçüm ve denetim sisteminin varlığı gerekir. Değişik amaçlar ve değişik uygulama alanlarına yönelik hazırlanmış perfor mans ölçüm ve denetim sistemlerinde kullanılabilecek ölçüm göstergeleri ve mo delleri vardır. Her sektör için uygulanabilecek tek bir performans ölçüm modeli yoktır. Burada önemli olan, modelin nasıl kullanılacağının ve sonuçlarının nasıl yorumlanacağının bilinmesidir. Son yıllarda yaygınca kullanılan“toplam perfor mans ölçüm modelleri”geliştirilmiştir. Çalışmanın uygulaması, sağlık sektörüne yönelik olmuştur. Bunun için; dört grup (SSK, üniversite, devlet ve özel) hastanenin aym-üratelerinin etkinlikleri Veri Zarflama Analizi (VZA) yöntemi ile ölçülerek değerlendirme yapılmıştır. - vıu
Özet (Çeviri)
SUMMARY PERFORMANCE MANAGEMENT SYSTEM AND APPLICATION OF DATA ENVELOPMENT ANALYSIS IN HEALTH CARE ORGANIZATIONS Performance management is a prime imperative for the 1990's. Today in industries, continuous improvement in quality performance is regarded as an indicator of overall performance. The study consists of four main parts. In the first part health servi ces system of Turkey is explained. The management policy and the existing situation in health care system in Turkey are mentioned. Consi dering these, not only the structure of organization and management but also the history of Turkish health policies is discussed. Subsequently medical staff, financial sources etc. in Turkey are investigated. Further more, hospitals within the health care organization are described. Cons equently, according to this analysis, serious administrative and technolo gical problems were found out in the hospitals in Turkey. Technological developments and demand increase in health care organizations, brought this sector to a position which spends most of sources. Therefore, it is very important to determine not only to what extend sources has been efficiently used by hospital and but also how to increase of the use the sources. The concept of performance and its use as a management tool are quite new for hospitals. In order to evaluate the existing situation and take related necessary precautions to improve medical services, there should be an established performance (productivity, efficiency, effecti veness, quality and so on) management system. Performance manage ment systems measure and follow up the productivity, efficiency etc. However, performance measurement in hospitals is quite difficult. For this reason, it presents great importance what is meant by performance in medical services. It shouldn't be interpreted that increase in producti vity of the hospitals can be reflected as on increase in examined, hospi talized and operated numbers of patients; or as an increase in the number of medical analysis, consumpted medicines and given doctors' reports etc. In order to improve the performance in the area of medical work, firstly the level of education has to be increased and secondly the use of -IXmodern technologies and facilities, mainly in the recruitment and mana gement of personnel and in every fields should be encouraged and finally every procedure, especially, the phase diagnoses, should be accelerated and management and convalescence should be improved where time is an input to the system. In the second part of the study, the definations and concepts in per formance management system, productivity, efficiency and effectivenes are explained. Performance management systems are expected to ensure adequate performance and improvement while simultaneously appraising perfor mance fairly and objectively, communicating the appraisal so that it is understood and appreciated, and turning the total process into a motiva tor to improve performance itself. Performance is a word which has different meanings. Although often used interchangeably, performance should not be confused with or perceived as productivity. Productivity is a measure of efficiency and effectiveness with which an organization produces goods and services. Performance means the actual accomplishment ofset of goals, objecti ves, duties, or responsibilities, as distinguished from potential ability, capacity, knowledge, skills, or aptitude to do so. Performance appraisal methodologies are techniques or tools to enhance or improve productivity. Many external and internal factors of an organization can affect this relationship between output and input, hence it can also affect the level of performance. Thus, it is important focus on performance in every kind of organizations. The process of performance management involves three major acti vities: planning and developing, implementing and monitoring, and evalu ating and realigning. This process is cyclical and constant. The performance management systen (PMS) is confused with the techniques of performance appraisal. The focus in this discussion is on the effectiveness of the performance management system rather than on the strengths and weaknesses of various appraisal techniques. Many good appraisal forms and techniques have been proposed, but they must be properly developed and correctly used if accurate performance assessments are to be made. There is no one perfect model of evaluating performance, because every sector has included its own features. For this reason, it is x-extremely difficult to be created a general purpose model within general purpose which includes all possible changes and relations. hi the third part of the study some performance measurement techni ques are explained. Generally, three approaches are used to evaluate performance, these are the followings: ratio analysis, parametrical methods, non-parametrical methods. Ratio analysis has been used to locate relationship that is abnor mally high or abnormally low. By in its nature, each ratio is limited to one output and one input, ant it cannot easily accommodate situations in which multiple inputs are used to produce multiple outputs. The second approach is regression analysis. Al thought it is more comprehensive than ratio analysis, there are a number of significant problems. Regress ion techniques reflect efficient relationship only when all the observation themselves are efficient. Regression techniques have been justified in industry studies, where profit maximization is believed to motivate all firms to operate at or near the efficient production frontiers. The third approach is non-parametrical models. These address the limitations associated with ratio analysis and regression techniques. These methods are appropriate with mathematical programming as a solution technique. Non-parametric efficiency measures have a very close relationship with performance concept. Especially, some models known as total performance measure models have become very popular during the last decade. These are resource allocation strategist (REALST), American productivity center method (APC), objective matrix method (OMAX). However, because of the purpose of the application is to measure the relative efficiency of hospitals which have the same decision making units, DEA is chosen. For this reason, DEA is explained in more detail. DEA was first demonstrated by Charnes, Cooper and Rhodes (1978). It measures the relative technical efficiency of a group of deci sion making units (DMUs) by simultaneously evaluating multiple inputs and outputs common the each unit. To use DEA, the analysist must first identify a group of DMUs with similar organizational goals and similar management decisions. Variables are then identified that represent DMU inputs and outputs related to efficiency. Next, the inputs are modelled as a weighted average as are the outputs and the ratio is formed of out puts over inputs. In the solution of DEA, the efficiency of unit is maxi mized subject to efficiencies of all the units in the set having an upper bound of 1. The efficiency of the unit will either equal 1 when it is efficient relative to the other units or will be less than 1 when the unit is inefficient. For an inefficient unit the solution identifies corresponding XIefficient units which are said to form a peer group for the inefficient unit. The last part of the study is a research which provides an illust rative application of Data Envelopment Analysis (DEA) methodology to the measurement of obstetrics and gynecology service efficiency at four group of Istanbul hospitals. Group includes state University, private and SSK hospitals. Data for this research were drawn from the department of the statis tics in hospitals, but some of the data are found from patient registra tions. The outputs are chosen as the number of the inpatient, the number of the inpatient days delivered, and the number of the patient applying to outpatient clinic. On the other hand three types of inputs are determined as the number of the beds, full-time equivalents physicians and nurses of the medical area. Certainly, there are other outputs produced by hospitals, including research, community service, and other health care goods and services and/or non-health care activities. Good measures of the latter types of output are, however, not available. Nevertheless, it is reasonable to assume that the above three capture the major outputs being produced by most hospitals. Study hospitals are profiled (The outputs and inputs) in Table 1. Table 1. Input and Output Data Used for DEA Evaluation of Obstetrics and Gynecology Services in Study Hospitals - xu -This list was refined by eliminating input measures, which were believed to be less directly associated with efficiency. The DEA results are summarized in Table 2, which indicates that hospitals Ç, C, G, I, and T are relatively inefficient compared with the other hospitals in the data set, that is, they achieve efficiency ratings of less than one. The meaning of the inefficient rating drived from DEA can be understood by examining the results for hospital Ç. DEA indicated that hospital Ç is inefficient, since comparison of hospital Ç with all eight hospitals gives an efficiency rating of 0.63. Table 2. Results of DEA Evaluating of Study Hospitals This rating means that hospital Ç should be able to produce its actual output level by using 37 percent - that is, (1.00 -0.63)x 100 - less of each input than it currently does. Such efficiency gains would reduce number of the beds, physicians and nurses in hospital Ç. DEA located and measured the inefficiency by comparing hospital Ç with its effici ency reference set (ERS) hospital Ş, A. ERS is the group hospitals against which DEA located the inefficient hospitals and the magnitude of the inefficiency. This information is a direct output of DEA. Manage ment of hospital Ç should focus on the management techniques used in hospital Ş and A to determine ways of reducing and improving its use of resources. This comparison is illustrated in Tablo 3., which indicates that a weighted composite of the efficiency reference set hospitals would yield a hypothetical hospital that would produce as much as outputs or more than the inefficient hospital Ç. In this example, the composite is constructed by applying the weights (the dual variables from the linear program) of 0.47461 and 0.83756, respectively, to the actual outputs and inputs of hospitals Ş and A. Columns 3,4 and 5 of Table 3 indicate that a combination of the actual operations of these two hospitals would -xni -result in a hypothetical hospital that would use 40 fewer beds, 21 fewer physicians and 12 fewer nurses to produce the same amount of patient days and 333 more units of patient than hospital Ç. Table 3. Comparison of Hospital Ç with its Efficiency Reference Set (Hospitals Ş and A) a Actual inputs and outputs per Table 1 b Weights (dual variables) from DEA The results of the DEA provides an option of selecting the opera ting changes to management. DEA has four advantages over the other techniques. First, DEA is particularly useful in hospital applications, because it can simultaneously accommodate multiple outputs and inputs and because it does not require specific knowledge of the efficient absolute or relative amount of inputs required for each hospital output. Second, the hospitals labeled as inefficient are strictly inefficient, and there is no problem of false identification of efficient hospitals as inefficient as long as all relevant outputs and inputs are included in the data set. Third, DEA indicates the general magnitude of the inefficien cies present in the inefficient hospitals. Fourth, DEA objectively locates inefficient hospitals without the need for an arbitrary cut off point, as in ratio analysis. xivDEA also has some limitations. First, DEA can only be used by comparing hospitals or hospital departments, because it locates only relatively inefficient units. Hence, it cannot locate all inefficient hospitals, because all hospitals in a given data set may be inefficient. This limitation also extends to regression techniques and to ratio analysis used to date. xv
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