Japanese surgical resource utilization in 2016

2019 ◽  
Vol 32 (6) ◽  
pp. 1013-1021
Author(s):  
Yoshinori Nakata ◽  
Yuichi Watanabe ◽  
Hiroto Narimatsu ◽  
Tatsuya Yoshimura ◽  
Hiroshi Otake ◽  
...  
Keyword(s):  
Resource Utilization ◽  
Electronic Medical Record System ◽  
Skin Incision ◽  
Efficiency Score ◽  
Academic Rank ◽  
Surgical Specialty ◽  
Record System ◽  
Content Type ◽  
Decision Making Unit ◽  
The Difference

Purpose The purpose of this paper is to examine from the viewpoint of resource utilization the Japanese surgical payment system which was revised in April 2016. Design/methodology/approach The authors collected data from surgical records in the Teikyo University electronic medical record system from April 1 till September 30, 2016. The authors defined the decision-making unit as a surgeon with the highest academic rank in the surgery. Inputs were defined as the number of medical doctors who assisted surgery, and the time of operation from skin incision to closure. An output was defined as the surgical fee. The authors calculated each surgeon’s efficiency score using output-oriented Charnes–Cooper–Rhodes model of data envelopment analysis. The authors compared the efficiency scores of each surgical specialty using the Kruskal–Wallis and the Steel method. Findings The authors analyzed 2,558 surgical procedures performed by 109 surgeons. The difference in efficiency scores was significant (p = 0.000). The efficiency score of neurosurgery was significantly greater than obstetrics and gynecology, general surgery, orthopedics, emergency surgery, urology, otolaryngology and plastic surgery (p<0.05). Originality/value The authors demonstrated that the surgeons’ efficiency was significantly different among their specialties. This suggests that the Japanese surgical reimbursement scales fail to reflect resource utilization despite the revision in 2016.

Resource utilization in surgery after the revision of surgical fee schedule in Japan

2015 ◽  
Vol 28 (6) ◽  
pp. 635-643 ◽  
Author(s):  
Yoshinori Nakata ◽  
Tatsuya Yoshimura ◽  
Yuichi Watanabe ◽  
Hiroshi Otake ◽  
Giichiro Oiso ◽  
...  
Keyword(s):  
Resource Utilization ◽  
Skin Incision ◽  
University Hospital ◽  
Academic Rank ◽  
Surgical Specialty ◽  
Content Type ◽  
Decision Making Unit ◽  
Using Data ◽  
Fee Schedule ◽  
Time Of Operation

Purpose – The purpose of this paper is to examine whether the current surgical reimbursement system in Japan reflects resource utilization after the revision of fee schedule in 2014. Design/methodology/approach – The authors collected data from all the surgical procedures performed at Teikyo University Hospital from April 1 through September 30, 2014. The authors defined the decision-making unit as a surgeon with the highest academic rank in the surgery. Inputs were defined as the number of medical doctors who assisted surgery, and the time of operation from skin incision to closure. An output was defined as the surgical fee. The authors calculated surgeons’ efficiency scores using data envelopment analysis. Findings – The efficiency scores of each surgical specialty were significantly different (p=0.000). Originality/value – This result demonstrates that the Japanese surgical reimbursement scales still fail to reflect resource utilization despite the revision of surgical fee schedule.

scholarly journals Equality of surgical fee schedule in Japan: a retrospective observational study

2021 ◽  
Author(s):  
Yoshinori Nakata ◽  
Yuichi Watanabe ◽  
Hiroshi Otake
Keyword(s):  
Data Envelopment Analysis ◽  
Efficiency Score ◽  
University Hospital ◽  
Academic Rank ◽  
Data Envelopment ◽  
Surgical Specialty ◽  
Gini Coefficients ◽  
Decision Making Unit ◽  
Significant Difference ◽  
Fee Schedule

Abstract Background The purpose of this study is to examine how the degree of inequality of Japanese surgical fee schedule changed during the study period by applying Gini coefficients for efficiency scores computed from data envelopment analysis. Methods All the surgeries that were performed in the main operating rooms of Teikyo University Hospital in 2013-18 were candidates used for the analysis of efficiency and equality of fee schedule. The decision making unit was defined as a surgeon with the highest academic rank in the surgery. Inputs were defined as (1) the number of assistants, and (2) the duration of operation. An output was defined as the surgical fee that was charged for reimbursement. Each surgeon’s efficiency score was calculated using data envelopment analysis. Using the medians of efficiency scores in each surgical specialty, the authors inferred Gini coefficients and their standard errors in each year and in each surgical fee schedule by the Bootstrap methods. Results The authors analyzed 16,307 surgical procedures during the study period of 2013-18. There was no statistically significant difference in the Gini coefficients between the years and between the surgical fee schedules (p > 0.05). Conclusions The authors demonstrated that the degree of inequality of Japanese surgical fee schedule remained constant from 2013 through 2018.

scholarly journals Association Between Surgeons’ Technical Efficiency and Hospital Revenue

2019 ◽  
Vol 56 ◽  
pp. 004695801988944
Author(s):  
Yoshinori Nakata ◽  
Yuichi Watanabe ◽  
Hiroshi Otake
Keyword(s):  
Regression Analysis ◽  
Multiple Regression Analysis ◽  
Multiple Regression ◽  
Technical Efficiency ◽  
Efficiency Score ◽  
University Hospital ◽  
Academic Rank ◽  
Surgical Volume ◽  
Surgical Specialty ◽  
Surgical Data

To evaluate surgeons’ performance, health care managers often use the revenues that surgeons make for the hospital. The purpose of this study is to determine the relationship between surgeons’ technical efficiency and their revenues by using multiple regression analysis on surgical data. The authors collected data from all the surgical procedures performed at University Hospital from April 1 through September 30 in 2013-2018. Output-oriented Charnes-Cooper-Rhodes model of data envelopment analysis was employed to calculate each surgeon’s technical efficiency. Seven independent variables were selected; revenue, experience, medical school, surgical volume, sex, academic rank, and surgical specialty. Multiple regression analysis using Tobit model was used for our data. The data from a total of 17 227 surgical cases were obtained in the 36-month study period. The authors performed multiple regression on 222 surgeons. Revenue had significantly positive association with mean efficiency score ( P = .000). Surgical volume had significantly negative association with mean efficiency score ( P = .000). The other coefficients were statistically insignificant. An increase in revenue by 1% was associated with 0.46% to 0.52% increases in efficiency score. We demonstrated that surgeons’ revenue can serve as a proxy variable for their technical efficiency.

Predictors of surgeons’ efficiency in the operating rooms

2016 ◽  
Vol 30 (1) ◽  
pp. 16-21 ◽  
Author(s):  
Yoshinori Nakata ◽  
Yuichi Watanabe ◽  
Hiroto Narimatsu ◽  
Tatsuya Yoshimura ◽  
Hiroshi Otake ◽  
...  
Keyword(s):  
Statistical Significance ◽  
Personal Characteristics ◽  
Positive Association ◽  
Efficiency Score ◽  
University Hospital ◽  
Academic Rank ◽  
Data Envelopment ◽  
Surgical Specialty ◽  
Independent Variables ◽  
Fee Schedule

The sustainability of the Japanese healthcare system is questionable because of a huge fiscal debt. One of the solutions is to improve the efficiency of healthcare. The purpose of this study is to determine what factors are predictive of surgeons’ efficiency scores. The authors collected data from all the surgical procedures performed at Teikyo University Hospital from April 1 through September 30 in 2013–2015. Output-oriented Charnes-Cooper-Rhodes model of data envelopment analysis was employed to calculate each surgeon’s efficiency score. Seven independent variables that may predict their efficiency scores were selected: experience, medical school, surgical volume, gender, academic rank, surgical specialty, and the surgical fee schedule. Multiple regression analysis using random-effects Tobit model was used for our panel data. The data from total 8722 surgical cases were obtained in 18-month study period. The authors analyzed 134 surgeons. The only statistically significant coefficients were surgical specialty and surgical fee schedule (p = 0.000 and p = 0.016, respectively). Experience had some positive association with efficiency scores but did not reach statistical significance (p = 0.062). The other coefficients were not statistically significant. These results demonstrated that the surgical reimbursement system, not surgeons’ personal characteristics, is a significant predictor of surgeons’ efficiency.

Efficiency and ranking of sustainability index of India using DEA-TOPSIS

2019 ◽  
Vol 11 (2) ◽  
pp. 179-199 ◽  
Author(s):  
Kiran Mehta ◽  
Renuka Sharma ◽  
Vishal Vyas
Keyword(s):  
Best Practices ◽  
Peer Group ◽  
Integrated Approach ◽  
Efficiency Score ◽  
Socially Responsible ◽  
Related Field ◽  
Content Type ◽  
Carbon Footprints ◽  
Decision Making Unit ◽  
Measuring Efficiency

PurposeThis study aims to assign efficiency score and then ranking the Indian companies known for best practices to control carbon-emission in the environment. It is destined to benchmark one company for best performance on the basis of selected alternatives among its peer group companies.Design/methodology/approachThe present study has used a hybrid model by applying data envelopment analysis (DEA)-technique for order performance by similarity to ideal solution (TOPSIS) to measure the efficiency and ranking of various decision units on the basis of specified variables.FindingsThe findings of DEA have given the best alternative or best decision-making unit (DMU) among the set of 25 DMUs considered for empirical testing. The DEA technique is used with TOPSIS, which is another popular multi-criteria decision model. The integrated DEA-TOPSIS model has helped to compute the efficiency score of all 25 DMUs of study and also provide a unique rank to each of the efficient unit identified with the help of DEA technique.Practical implicationsThe findings of the study have provided Benchmark Company amongst the companies following best practices for saving energy and having best operating profits too. This benchmark business unit can be studied extensively by peer group companies to compare various parameters affecting their efficiency and profits both.Social implicationsThe findings of the study will promote the socially responsible practices by corporate citizens and adopt the practices to reduce their carbon footprints. It will also suggest to socially responsible investors to select the benchmark and most efficient companies for investment purpose.Originality/valueThe study is original in terms of measuring efficiency and ranking of companies known for best practices for controlling their carbon footprints and suggesting a benchmark company to its peer group. Also, the integrated approach of using DEA-TOPSIS for such type of studies also makes it distinctive from earlier work done in the related field.

Developing an inverse range directional measure model to deal with positive and negative values

2019 ◽  
Vol 57 (9) ◽  
pp. 2520-2540 ◽  
Author(s):  
Sara Yousefi ◽  
Reza Farzipoor Saen ◽  
Seyed Shahrooz Seyedi Hosseininia
Keyword(s):  
Supply Chains ◽  
Cash Flow ◽  
Efficiency Score ◽  
Negative Data ◽  
Flow Management ◽  
Content Type ◽  
Cash Flow Management ◽  
Input And Output ◽  
Decision Making Unit ◽  
Dea Models

Purpose To manage cash flow in supply chains, the purpose of this paper is to propose inverse data envelopment analysis (DEA) model. Design/methodology/approach This paper develops an inverse range directional measure (RDM) model to deal with positive and negative values. The proposed model is developed to estimate input and output variations such that not only efficiency score of decision making unit (DMU) remains unchanged, but also efficiency score of other DMUs do not change. Findings Given that auto making industry deals with huge variety and volumes of parts, cash flow management is so important. In this paper, inverse RDM models are developed to manage cash flow in supply chains. For the first time, the authors propose inverse DEA models to deal with negative data. By applying the inverse DEA models, managers distinguish efficient DMUs from inefficient ones and devise appropriate strategies to increase efficiency score. Given results of inverse integrated RDM model, other combinations of cash flow strategies are proposed. The suggested strategies can be taken into account as novel strategies in cash flow management. Interesting point is that such strategies do not lead to changes in efficiency scores. Originality/value In this paper, inverse input and output-oriented RDM model is developed in presence of negative data. These models are applied in resource allocation and investment analysis problems. Also, inverse integrated RDM model is developed.

scholarly journals Leading change: introducing an electronic medical record system to a paramedic service

2016 ◽  
Vol 29 (2) ◽  
pp. 136-150 ◽  
Author(s):  
Shawn Baird ◽  
George Boak
Keyword(s):  
User Interfaces ◽  
Emergency Care ◽  
Electronic Medical Record System ◽  
Ease Of Use ◽  
Care Organization ◽  
Perceived Ease Of Use ◽  
Structured Interviews ◽  
Record System ◽  
Content Type ◽  
Emergency Medical

Purpose Leaders in health-care organizations introducing electronic medical records (EMRs) face implementation challenges. The adoption of EMR by the emergency medical and ambulance setting is expected to provide wide-ranging benefits, but there is little research into the processes of adoption in this sector. The purpose of this study is to examine the introduction of EMR in a small emergency care organization and identify factors that aided adoption. Design/methodology/approach Semi-structured interviews with selected paramedics were followed up with a survey issued to all paramedics in the company. Findings The user interfaces with the EMR, and perceived ease of use, were important factors affecting adoption. Individual paramedics were found to have strong and varied preferences about how and when they integrated the EMR into their practice. As company leadership introduced flexibility of use, this enhanced both individual and collective ability to make sense of the change and removed barriers to acceptance. Research limitations/implications This is a case study of one small organization. However, there may be useful lessons for other emergency care organizations adopting EMR. Practical implications Leaders introducing EMR in similar situations may benefit from considering a sense-making perspective and responding promptly to feedback. Originality/value The study contributes to a wider understanding of issues faced by leaders who seek to implement EMRs in emergency medical services, a sector in which there has been to date very little research on this issue.

Evaluating after-sales service units by developing inverse network data envelopment analysis model

2019 ◽  
Vol 27 (2) ◽  
pp. 695-707 ◽  
Author(s):  
Reza Farzipoor Saen ◽  
Seyed Shahrooz Seyedi Hosseini Nia
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Efficiency Score ◽  
Data Envelopment Analysis Model ◽  
Network Data ◽  
Data Envelopment ◽  
Analysis Model ◽  
Content Type ◽  
Network Data Envelopment Analysis ◽  
Decision Making Unit

Purpose The purpose of this paper is to develop an inverse network data envelopment analysis (INDEA) model to solve resource allocation problems. Design/methodology/approach The authors estimate inputs’ variations based on outputs so that the efficiencies of decision-making unit under evaluation (DMUo) and other decision-making units (DMUs) are constant. Findings The new INDEA model is developed to allocate resources such that inputs are not increased while efficiency scores of all DMUs remain constant. Furthermore, the authors obtain new combinations of inputs and outputs, together with a growth in efficiency score of DMUo such that efficiency scores of other DMUs are not changed. A case study is provided. Originality/value This paper proposes INDEA model to estimate inputs (outputs) without changing efficiency scores of DMUs.

Evaluation of the resource utilization efficiency of university libraries using DEA techniques and a proposal of alternative evaluation variables

2011 ◽  
Vol 29 (4) ◽  
pp. 697-724 ◽  
Author(s):  
Younghee Noh
Keyword(s):  
Technical Efficiency ◽  
Resource Utilization ◽  
Utilization Efficiency ◽  
University Libraries ◽  
Electronic Resources ◽  
Content Type ◽  
The Difference ◽  
Resource Utilization Efficiency ◽  
Efficiency Rate ◽  
Percent Efficiency

PurposeThis paper seeks to rediscover the most suitable efficiency evaluation variables (input and output variables) for digital libraries and to employ the data envelopment analysis (DEA) model to measure the resource utilization efficiency of university libraries.Design/methodology/approachIn order to analyze and evaluate university library efficiency, the paper introduces the DEA‐CCR Model and the DEA‐BCC Model. Based on these research tools, the Technical Efficiency (CCR*BCC) was determined. First, a reference group was created with a 100 percent efficiency rate, then the factors contributing to inefficient DMUs were analyzed, and the difference in the efficiency rate compared according to the different governing bodies of the libraries. Finally, the difference of efficiency according to the introduction and rejection of electronic resources was analyzed. It was possible to measure the technical efficiency, pure‐technical efficiency, and scale efficiency.FindingsThe results showed that the efficiency of university libraries varied significantly according to whether or not electronic resources were included in the evaluation. In addition, the findings confirmed decision making units (DMUs) have a 100 percent efficiency rate and a low efficiency rate as well as proposed benchmarking DMUs for inefficient DMUs and a direction for future improvements.Originality/valueThe paper identifies that there was a significant difference in efficiency, according to the presence of electronic resources in university libraries.

scholarly journals Vital Signs Are Not Associated with Self-Reported Acute Pain Intensity in the Emergency Department

CJEM ◽  
2015 ◽  
Vol 18 (1) ◽  
pp. 19-27 ◽  
Author(s):  
Raoul Daoust ◽  
Jean Paquet ◽  
Benoit Bailey ◽  
Gilles Lavigne ◽  
Éric Piette ◽  
...  
Keyword(s):  
Emergency Department ◽  
Pain Intensity ◽  
Health Care Professionals ◽  
Vital Signs ◽  
Total Sample ◽  
Electronic Medical Record System ◽  
Fracture Dislocation ◽  
Record System ◽  
Significant Pain ◽  
The Difference

AbstractObjectivesThis study aimed to ascertain the association between self-reported pain intensity and vital signs in both emergency department (ED) patients and a subgroup of patients with diagnosed conditions known to produce significant pain.MethodsWe performed a retrospective analysis of real-time, archived data from an electronic medical record system at an urban teaching hospital and regional community hospital. We included consecutive ED patients ≥16 years old who had a self-reported pain intensity ≥1 as measured during triage, from March 2005 to December 2012. The primary outcome was vital signs for self-reported pain intensity levels (mild, moderate, severe) on an 11-point verbal numerical scale. Changes in pain intensity levels were also compared to variations in vital signs. Both analyses were repeated on a subgroup of patients with diagnosed conditions recognized to produce significant pain: fracture, dislocation, or renal colic.ResultsWe included 153,567 patients (mean age of 48.4±19.3 years; 55.5% women) triaged with pain (median intensity of 7/10±3). Of these, 8.9% of patients had diagnosed conditions recognized to produce significant pain. From the total sample, the difference between mild and severe pain categories was 2.7 beats/minutes (95% CI: 2.4−3.0) for heart rate and 0.13 mm Hg (95% CI: -0.26−0.52) for systolic blood pressure. These differences generated small effect sizes and were not clinically significant. Results were similar for patients who experienced changes in pain categories and for those conditions recognized to produce significant pain.ConclusionHealth care professionals cannot use vital signs to estimate or substantiate self-reported pain intensity levels or changes over time.

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