Songul Cinaroglu

Complexity in healthcare management: Why does Drucker describe healthcare organizations as a double-headed monster?

Abstract The sector of healthcare management is different from other sectors because of its complexity. The reason of this complexity is that there are two different professional aspects of this sector i.e. medical and non-medical. Medical professionals are more familiar with biomedical terms and knowledge than non-medical professionals. On the other hand, non-medical professionals are as qualified as medical professionals and are educated in managing different functions of organization and work with a broader perspective. Due to this two-sided nature, Drucker describes difficulties in healthcare management as a ‘two-headed monster’. This study discusses the complexity in healthcare management, particularly in terms of this two-sided nature.

Understanding the relationship between effectiveness and outcome indicators to improve quality in healthcare

Healthcare institutions face significant challenges in implementing quality initiatives such as performance measurement. In the wake of multiple studies emphasising deficiencies in performance measurement in healthcare, measuring the performance of healthcare services to improve quality takes a great attention in the literature. Understanding the relationships between performance indicators is a first step for this. Effectiveness, which is one of the performance indicators in healthcare, reflects the effect of health interventions on health outcomes. Accessibility of services and utilisation are the two main dimensions of this concept. These indicators have the potential for improving outcomes, performance, and quality in health. This study explores the relationship between effectiveness and health outcome indicators as they relate to the development level and geographic region of 81 provinces in Turkey using a path analytic model. The numbers of hospitals and physicians are used as indicators of accessibility of healthcare services, while the average length of stay and number of surgical operations are used as indicators of utilisation. Life expectancy and general satisfaction from healthcare services are determined as outcome measures. According to the final path model, a strong relationship exists between accessibility indicators and health outcomes. A strong relationship was also found between life expectancy and general satisfaction with healthcare services, which are the objective and subjective outcome measures in healthcare, respectively. These results help our understanding of the relationship among key performance measures to improve health systems performance and quality.

Explanatory Factors of Quality of Care from Cataract Patients’ Perspectives

ABSTRACT Purpose: The purpose of this study is to examine explanatory factors of perceived quality of care among cataract surgery patients. Methods: This study was administered to 264 cataract patients within one eye hospital located in Ankara, Turkey. The study was designed to determine the latent structure of quality of care. In order to assess cataract surgery patients’ views about quality of care, the QUOTE-Cataract survey was used. The questionnaire’s internal consistency was assessed using Cronbach’s Alpha (0.96) and appropriateness of the factor analytic model was assessed using KMO (0.50) and Bartlett’s test (=2004.959, p<0.001). Explanatory factor analysis with Varimax rotation was performed in order to determine the underlying factors in the model. Results: Four factors emerge from the explanatory factor analysis: relaying information about care process and behaviors; diagnosis and treatment process; accessibility/punctuality of physicians; and hospital facilities. The four factors explain 86% of total variance. Conclusion: The results of this study highlight the importance of sharing information with patients about treatment processes and accessibility/punctuality of physicians in the perception of quality of care among cataract surgery patients.

Demographic and Welfare State Predictors of Out-of-Pocket Health Expenditures: A Path Analytic Model

ABSTRACT Out-of-pocket (OOP) payments are principal components of financing healthcare and have a significant effect on poverty in numerous developing countries. The present study seeks to ascertain the relation among demographic, welfare state, and OOP health expenditure indicators using a path analysis. National representative household budget data from the Turkish Statistical Institute for 2015 were used. To test the goodness of fit of the model, multiple fit indices were utilized. The model fit for redefined path analytic model data was good (X2/df = 70.20/9 = 7.8; RMSEA = 0.032; GFI = 1.00; AGFI = 0.99; CFI = 0.99). The results of the analysis revealed that demographic and welfare indicators are causally related to OOP health expenditures, and income was a mediating factor for this interrelationship. Designing of socially inclusive policies on the basis of the values of equity is essential to combat poverty due to OOP health expenditures in developing countries.

Socio-economic status and self-rated health: Are they good predictors of income? An analysis of survey panel data from Turkey

Background: The socioeconomic dynamics and economic status of households are changing rapidly all over the world, especially for middle-income and developing countries such as Turkey. It is well known that income is one of the most important determinants of socioeconomic status (SES) and health. There is a need to analyze changing trends and relationships among SES variables over time. Unfortunately, such changes remain undetected in cross-sectional studies. However, panel data cover multiple sequential time periods for the same firms or individuals and allow analysis of these changing patterns. Objectives: This study aims to determine predictive factors of income on a decision tree and to observe changes of predictive role of SES and health indicators over time, to predict income using three different panel datasets. Materials and Methods: Data from the Income and Living Conditions Survey in Turkey between 2008 and 2011 were used. A random effects and expectation maximization tree algorithm were also used in the analysis. Results: This study results show that education is the variable that is the most influential in predicting income between 2008 and 2011 and between 2009 and 2011; on the other hand, current economic status is a determining factor of income between 2010 and 2011. Conclusion: Experimental results highlight that education outperforms SES and health indicators in the prediction of personal income.

Comparison of Medical and Surgical Nurses Attitudes toward Usage ofElectronic Health Records

Background: Health care is an organizational field that information and technology improves quickly. With ensuring health professionals adaptation to this new information and technology environment, it is possible to achieve quality and productivity improvement goal in health care. It is known that different clinical expertises bring differences in presentation of health services. Aim: In this study it was aimed to compare nurses’ assessments about electronic health records usage. Materials and methods: Data analyzed by using descriptive statistics, Chi-square test and independent sample student-t test. Results: At the end of the analysis it was found that nurses’ assessments about electronic health records usage has a meaningful difference according to different clinical expertise (t=2.40, p < 0.05). Conclusion: Results of this study shows that surgical nurses’ who are forefront with “technical abilities” have more positive assessments about usage of electronic health records when they compared with medical nurses who are forefront with “patient centered” abilities.