Tsung-Tai Chen

The Unintended Consequence of Diabetes Mellitus Pay‐for‐Performance (P4P) Program in Taiwan: Are Patients with More Comorbidities or More Severe Conditions Likely to Be Excluded from the P4P Program?

OBJECTIVE Taiwan has instituted a pay-for-performance (P4P) program for diabetes mellitus (DM) patients that rewards doctors based in part on outcomes for their DM patients. Doctors are permitted to choose which of their DM patients are included in the P4P program. We test whether seriously ill DM patients are disproportionately excluded from the P4P program. DATA SOURCE/STUDY SETTING This study utilizes data from the National Health Insurance (NHI) database in Taiwan for the period of January 2007 to December 2007. Our sample includes 146,481 DM-P4P patients (16.56 percent of the total) and 737,971 non-DM-P4P patients. DATA COLLECTION/EXTRACTION METHODS We use logistic and multilevel models to estimate the effects of patient and hospital characteristics on P4P selection. PRINCIPAL FINDINGS The results show that older patients and patients with more comorbidities or more severe conditions are prone to be excluded from P4P programs. CONCLUSIONS We found that DM patients are disproportionately excluded from P4P programs. Our results point to the importance of mandated participation and risk adjustment measures in P4P programs.

The use of statistical process control (risk-adjusted CUSUM, risk-adjusted RSPRT and CRAM with prediction limits) for monitoring the outcomes of out-of-hospital cardiac arrest patients rescued by the EMS system

OBJECTIVE Based on previous experience from surgical surveillance, risk-adjusted cumulative sum (CUSUM)-type charts were applied to monitor out-of-hospital cardiac arrest (OHCA) patient mortality. MATERIALS AND METHODS Data from 2356 OHCA patients were collected by the Taipei County Fire Bureau from June 2006 to November 2007. Logistic regression analysis was applied to create a risk-adjusted model. Next, a risk-adjusted CUSUM chart, a risk-adjusted resetting sequential probability ratio test chart and a cumulative risk-adjusted mortality with prediction limits chart were used to detect excess deaths of the OHCA patients rescued by the emergency medical service (EMS) system. RESULTS The overall mortality rate, defined as having no return of spontaneous circulation, was 79.3%. These three charts signalled an increase in the death rate at similar sites, and also suggested a small process shift. CONCLUSION A visual approach to EMS systems monitoring that combines the risk-adjusted cumulative sum, Risk-adjusted resetting sequential probability ratio test and cumulative risk-adjusted mortality with prediction limits charts was established. It was found that this approach can be effectively used by the EMS community to monitor OHCA outcomes in real time.

A model measuring therapeutic inertia and the associated factors among diabetes patients: A nationwide population‐based study in Taiwan

This article presents an analysis conducted on the patterns related to therapeutic inertia with the aim of uncovering how variables at the patient level and the healthcare provider level influence the intensification of therapy when it is clinically indicated. A cohort study was conducted on 899,135 HbA1c results from 168,876 adult diabetes patients with poorly controlled HbA1c levels. HbA1c results were used to identify variations in the prescription of hypoglycemic drugs. Logistic regression and hierarchical linear models (HLMs) were used to determine how differences among healthcare providers and patient characteristics influence therapeutic inertia. We estimated that 38.5% of the patients in this study were subject to therapeutic inertia. The odds ratio of cardiologists choosing to intensify therapy was 0.708 times that of endocrinologists. Furthermore, patients in medical centers were shown to be 1.077 times more likely to be prescribed intensified treatment than patients in primary clinics. The HLMs presented results similar to those of the logistic model. Overall, we determined that 88.92% of the variation in the application of intensified treatment was at the within‐physician level. Reducing therapeutic inertia will likely require educational initiatives aimed at ensuring adherence to clinical practice guidelines in the care of diabetes patients.

Statistical process control as a tool for controlling operating room performance: retrospective analysis and benchmarking

BACKGROUND There is much research using statistical process control (SPC) to monitor surgical performance, including comparisons among groups to detect small process shifts, but few of these studies have included a stabilization process. This study aimed to analyse the performance of surgeons in operating room (OR) and set a benchmark by SPC after stabilized process. METHODS The OR profile of 499 patients who underwent laparoscopic cholecystectomy performed by 16 surgeons at a tertiary hospital in Taiwan during 2005 and 2006 were recorded. SPC was applied to analyse operative and non-operative times using the following five steps: first, the times were divided into two segments; second, they were normalized; third, they were evaluated as individual processes; fourth, the ARL(0) was calculated;, and fifth, the different groups (surgeons) were compared. Outliers were excluded to ensure stability for each group and to facilitate inter-group comparison. RESULTS The results showed that in the stabilized process, only one surgeon exhibited a significantly shorter total process time (including operative time and non-operative time). CONCLUSION In this study, we use five steps to demonstrate how to control surgical and non-surgical time in phase I. There are some measures that can be taken to prevent skew and instability in the process. Also, using SPC, one surgeon can be shown to be a real benchmark.

The relationship between survival after out-of-hospital cardiac arrest and process measures for emergency medical service ambulance team performance

OBJECTIVE International institutes have developed their own clinical performance indicators for ambulance services. It is unknown whether these process measures are related to survival of patients after out-of-hospital cardiac arrest (OHCA). We aimed to determine whether Emergency Medical Service (EMS)-related ambulance team process measures correlate with patient survival. METHODS Four years of observational data were collected from an urban EMS OHCA registry. The two process measures were achieving an EMS response time ≤4 min and prehospital ROSC (return of spontaneous circulation). The outcome measure was survival to discharge. We used the GLMM (generalised linear mixed model) with stepwise selection to examine this process-outcome link at the patient and EMS team levels, respectively. RESULTS We analyzed 3856 OHCA patients distributed across forty-three EMS ambulance teams. Survival to discharge was observed in 193 (5%) patients. The two EMS team process measures were positively associated with an improvement in survival at the patient level after case-mix adjustment. However, they were not associated with improvement in the risk-adjusted survival rate. CONCLUSIONS The EMS team-level process measures proposed by international institutes may not predict the risk-adjusted survival rate. Using these measures to motivate EMS teams to improve their quality performance would be questionable. Increased efforts should be devoted to constructing more pivotal EMS team-level process measures that are tightly linked to survival.

Participating physician preferences regarding a pay-for-performance incentive design: a discrete choice experiment

OBJECTIVE To determine whether the magnitude of incentives or other design attributes should be prioritized and the most important attributes, according to physicians, of the diabetes P4P (pay-for-performance) program design. DESIGN We implemented a discrete choice experiment (DCE) to elicit the P4P incentive design-related preferences of physicians. PARTICIPANTS All of the physicians (n = 248) who participated in the diabetes P4P program located in the supervisory area of the northern regional branch of the Bureau of National Health Insurance in 2009 were included. The response rate was ∼ 60%. RESULTS Our research found that the bonus type of incentive was the most important attribute, followed by the incentive structure and the investment magnitude. CONCLUSIONS Physicians may feel that good P4P designs are more important than the magnitude of the investment by the insurer. The two most important P4P designs include providing the bonus type of incentive and using pay-for-excellence plus pay-for-improvement.

Exploring and comparing the characteristics of nonlatent and latent composite scores: implications for pay-for-performance incentive design.

A concise and reliable composite quality score would be helpful in judging the quality of a hospital’s services, especially for pay-for-performance (P4P) initiatives. This study compared several nonlatent and latent composite quality scores to evaluate the quality of care using diabetes mellitus (DM) P4P data and discusses their characteristics and implications for P4P policy. The authors describe a cross-sectional study of the DM P4P data collected from the claims data of the Bureau of National Health Insurance (NHI) in Taiwan from January 2007 to December 2007. The DM patient outcome data, such as hemoglobin A1C values, were retrieved from the P4P database sponsored by the Bureau of NHI in Taiwan. The composite scores were derived from the following methods: 1) nonlatent scores methods (e.g., the raw sum score and the all-or-none score methods)and 2) latent scores methods (e.g., item-response theory-based Models I and II and the PRIDIT model). These scores are compared in terms of 2 aspects—agreement of hospital rankings (using Spearman’s rank correlation) and reliability (using bootstrap methods). The latent methods were superior to the nonlatent methods because they were more reliable and had specific weighting themes. The correlations among the 3 latent methods were moderately high. The use of the PRIDIT approach, which is moderately difficult compared with item response theory–based model, is recommended if the insurer wants to balance convenience and precision.

The Unintended Consequences Of Pay-For-Performance

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