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Prevention of surgical site infections (SSIs) is a critical aspect of ensuring positive patient outcomes. One of the challenges of SSI prevention is the communication barrier between perioperative staff members and infection preventionists (IPs), which may lead to frontline staff members who are primarily responsible for infection prevention being unaware of pertinent hospital SSI data. To overcome this challenge, IPs and perioperative staff members should develop a partnership that facilitates the sharing of feedback on SSI case review data and effective key performance indicators. A partnership also can help engage perioperative staff members in quality improvement efforts and increase collaboration with IPs. Perioperative leaders should identify effective methods to improve data transparency, SSI case reviews, audit and feedback programs, and education for perioperative team members. A strong perioperative-IP partnership and increased sharing of data in accessible formats may improve engagement and interest in SSI prevention.

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Leaders in perioperative and interventional procedure areas need to be able to initiate and sustain change to improve operational processes in their departments or service lines. Although available literature discusses change in health care organizations, there is a lack of published articles on the implementation and sustainment of change. This article provides a review of supporting literature on change management and an infrastructure model that we have successfully implemented to sustain change. An organizational case study focused on creating sustained improvements for first procedure on-time starts and turnover times details the process of creating the accountability system for actualizing the performance targets in a perioperative environment. The case study examines the existing process and initial challenges with creating sustainable and quantifiable outcomes, describes the process of implementing the infrastructure discussed in the article, and evaluates the results. Perioperative leaders can use the information to improve processes in their work environments.

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Performance analysis is an important way for hospitals to achieve higher efficiency and effectiveness in providing services to their customers. The performance of the healthcare system can be measured by many indicators, but it is difficult to improve them simultaneously due to the limited resources. A feasible way is to identify the central and influential indicators to improve healthcare performance in a stepwise manner. In this paper, we propose a hybrid multiple criteria decision making (MCDM) approach to identify key performance indicators (KPIs) for holistic hospital management. First, through integrating evidential reasoning approach and interval 2-tuple linguistic variables, various assessments of performance indicators provided by healthcare experts are modeled. Then, the decision making trial and evaluation laboratory (DEMATEL) technique is adopted to build an interactive network and visualize the causal relationships between the performance indicators. Finally, an empirical case study is provided to demonstrate the proposed approach for improving the efficiency of healthcare management. The results show that "accidents/adverse events", "nosocomial infection", ''incidents/errors", "number of operations/procedures" are significant influential indicators. Also, the indicators of "length of stay", "bed occupancy" and "financial measures" play important roles in performance evaluation of the healthcare organization. The proposed decision making approach could be considered as a reference for healthcare administrators to enhance the performance of their healthcare institutions.

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Key performance indicators (KPIs) are critical for manufacturing operation management and continuous improvement (CI). In modern manufacturing systems, KPIs are defined as a set of metrics to reflect operation performance, such as efficiency, throughput, availability, from productivity, quality and maintenance perspectives. Through continuous monitoring and measurement of KPIs, meaningful quantification and identification of different aspects of operation activities can be obtained, which enable and direct CI efforts. A set of 34 KPIs has been introduced in ISO 22400. However, the KPIs in a manufacturing system are not independent, and they may have intrinsic mutual relationships. The goal of this paper is to introduce a multi-level structure for identification and analysis of KPIs and their intrinsic relationships in production systems. Specifically, through such a hierarchical structure, we define and layer KPIs into levels of basic KPIs, comprehensive KPIs and their supporting metrics, and use it to investigate the relationships and dependencies between KPIs. Such a study can provide a useful tool for manufacturing engineers and managers to measure and utilize KPIs for CI.

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While the solute clearance marker (Kt/Vurea ) is widely used, no effective marker for volume management exists. Two principles apply to acute volume change in hemodialysis: (1) the plasma refill rate, the maximum rate the extracellular fluid can replace a contracting intravascular volume (±5 mL/kg/hour) and (2) the rate of intravascular volume contraction where coronary hypoperfusion, myocardial stun, and vascular risk escalates (observed at ≥10 mL/kg/hour). In extended hour and higher frequency hemodialysis, intravascular contraction rates are usually equilibrated by the plasma refill rate, but in "conventional" in-center hemodialysis, volume contraction rates commonly exceed the capabilities of the plasma refill rate, resulting in inevitable hypovolemia. To minimize cardiovascular risk, fluid removal rates should ideally be ≤10 mL/kg/hour, acknowledging that this may be challenging in the in-center setting. Two options exist to limit volume removal to >10 mL/kg/hour: restricting interdialytic weight gain (always conflict-fraught, often unachievable) or extending sessional duration to allow additional removal time. Just as Kt/Vurea quantifies solute removal, a simple-to-apply rate variable should also apply for volume removal. As predialysis and target postdialysis weights are both known, a simple measure--a maximum rate for ultrafiltration (UFRmax )--would advise the sessional duration (T) required to minimize organ stun by removing the required fluid load (V) from any patient of predialysis weight (W). This would ensure a removal rate no greater than 10 mL/kg/hour-T (hours) = V (mL)/10 × W (kg). Used together, Kt/Vurea and UFRmax would form a solute and volume composite, each dialysis treatment continuing until both solute and volume requirements are fulfilled.

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The objectives of this study were to assign reasonability to importance of weight selection issue in key performance indicator for performance evaluation of Centers for Child-care Foodservice Management (CCFSM) developed by using Balanced Scorecard (BSC), to draw key performance indicator (KPI) by perspective and to analyze differences in recognition on importance. From September 25 to October 9, 2012, we conducted a questionnaire-based study via e-mail, targeting chiefs and team leaders of nationwide 21 CCFSMs (43 persons), officials of local governments where CCFSM was established (21 persons), officials of Korea Food and Drug Administration (2 persons) and foodservice management experts (27 persons) in order to estimate the relative importance on 4 perspectives and 14 KPIs and analyzed its results by using 61 collected data. The results showed that relative importance of perspectives was estimated in order of importance as follows: business performance (0.3519), customer (0.3393), resource (0.1557), learning and growth (0.1531). Relative importance of KPIs was in order of importance as follows: Evaluation of sanitary management level in childcare foodservice facilities (0.1327), Level of customer recognition and behavior improvement (0.1153), performances of round visiting inspection on foodservice, sanitary, safety management, and foodservice consulting (0.0913). Our results showed that the recognition differences exist on the relative importance of perspectives and KPIs between officials of CCFSM, KFDA, local government and foodservice management experts. These observations will form the basis for developing evaluation systems, and it is considered that performance indicators developed on this basis will suggest direction of operation which CCFSM will have to perform.

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Patient waiting time was introduced to orthodontic clinics in 2009 as a Key Performance Indicator (KPI) in the Ministry of Health Malaysia (MOH) as a measure of client satisfaction. A cross-sectional pilot study was carried out in 2009 in all four main government orthodontic clinics in Selangor. The objectives were to measure patient actual waiting time and evaluate conformance to this KPI. The sample comprised of 5,286 patients; 9.2% from Tanjung Karang, 37.1% Kajang, 29.3% Klang and 24.4% Shah Alam. There were 33.8% punctual, 44.2% early and 21.9% late patients. The mean actual waiting time (AWT) in Selangor was 30 min (SD 24.7); shortest in Tanjung Karang (16.5min, SD 15.3) and longest in Shah Alam (47.9min, SD29.6). AWT was 21.9 min (SD 17.4) for patients punctual for appointments, 40.3 min (SD 40.3) for early patients and 21.9min (SD19.8) for late patients respectively. Although the mean AWT was long for early patients, 20% of them were seen earlier than their appointment time. All four clinics complied with the MOH KPI performance target (>50%) with a mean compliance of 87.5% for Selangor. There is statistically significant difference in punctuality of patients in different clinics (p<0.0001) and in KPI conformance between clinics (p<0.0001).