Spiritual leadership influence on employee creative service performance: a moderated mediation analysis.

This paper expands the understanding of the relationship between spiritual leadership (SPL) and the creative service performance of employees. The research model, based on cognitive evaluation theory, examines the mediating role of employee autonomy and the moderating role of proactive personality in the relationship between SPL and employee creative service performance. Data was collected from 351 employees in China to test the moderated mediation model of this study. The empirical analysis reveals a positive association between SPL and employee autonomy, which in turn leads to increased employee creative service performance. Furthermore, the results show that SPL indirectly affects employee creative service performance via employee autonomy. Additionally, the findings suggest that a proactive personality can enhance the direct effect of SPL on employee autonomy and the indirect effect of SPL on employee creative service performance via employee autonomy. These results contribute significantly to the literature on SPL and creativity. The contributions and implications of this study are discussed in the subsequent section.

Validation of coding algorithms for identifying people with viral hepatitis using claims data according to different standard references.

BACKGROUND: To assess the performance of various coding algorithms for identifying people with hepatitis B virus (HBV) and hepatitis C virus (HCV) using claims data according to different reference standards (RSs) and study periods (SPs). METHODS: A proportional random sampling of 10,000 patients aged ≥ 20 years in a health care system in Southern Taiwan were enrolled as study participants. We used three hierarchical RSs (RS1: having positive results of laboratory tests; R2: having RS1 or having prescriptions of anti-HBV or anti-HCV medications; R3: having R1 or R2 or having textual diagnosis recorded in electrical medical records) with three SPs (4-, 8-, and 12-years) to calculate positive predictive value (PPV) and sensitivity (Sen) of 6 coding algorithms using HBV- and HCV-related International Classification of Disease Tenth Revision Clinical Modification (ICD-10-CM) codes in Taiwan National Health Insurance claims data for years 2016-2019. RESULTS: Of 10,000 enrolled participants, the number of participants had confirmed HBV and HCV was 146 and 165, respectively according to RS1 with 4-years SP and increased to 729 and 525, respectively according to RS3 with 12-years SP. For both HBV and HCV, the PPV was lowest according to RS1 and highest according to RS3. The longer the SP, the higher the PPV. However, the Sen was highest according to RS2 with 4-years SP. For both HBV and HCV, the coding algorithm with highest PPV and Sen was " ≥ 3 outpatient codes" and " ≥ 2 outpatient or ≥ 1 inpatients codes," respectively. CONCLUSIONS: In conclusion, using different RSs with different SPs would result in different estimation of PPV and Sen. To achieve the best yield of both PPV and Sen, the optimal coding algorithm is " ≥ 2 outpatients or ≥ 1 inpatients codes" for identifying people with HBV or HCV.

Existing Data Sources in Clinical Epidemiology: The Taiwan National Health Insurance Laboratory Databases.

This paper provides an introduction to laboratory databases established by Taiwan National Health Insurance Administration (NHIA) since 2015 and released for research since June 2017. The National Health Insurance (NHI) is a government-run single-payer program introduced in 1995 that now covers more than 99% of 23 million Taiwanese citizens. To prevent duplication of medication prescriptions and laboratory test and examination prescriptions, contracted health care providers are required to upload the results of laboratory tests and reports of examinations to the NHIA. The cumulative number of laboratory test results was 5.64 billion from January 2015 to the end of August 2020 for 602 types of test. There are 35 variables for each laboratory test result stored in the databases that can be used for research. However, different hospitals might use different format in reporting the results. The researchers therefore have to develop algorithms to include and exclude incompatible records and to determine whether the results are positive or negative (normal or abnormal). The NHIA suggests that researchers release their source codes of algorithms so that other researchers can modify the codes to improve inter-study comparability. Through the unique personal identification number, the laboratory data can be linked to NHI inpatient and outpatient claims data for further value-added analyses. Non-Taiwanese researchers can collaborate with Taiwan researchers to access the NHI laboratory databases.

Validity of ICD-10-CM Codes Used to Identify Patients with Chronic Hepatitis B and C Virus Infection in Administrative Claims Data from the Taiwan National Health Insurance Outpatient Claims Dataset.

PURPOSE: To validate the use of International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes to identify patients with chronic hepatitis B virus (HBV) and hepatitis C virus (HCV) infection in the Taiwan National Health Insurance (NHI) Outpatient Claims Dataset. METHODS: We conducted a retrospective study using results of HBV surface antigen (HBsAg), HBV e antigen (HBeAg), and anti-HCV antibody tests in the NHI Lab & Exam Dataset from January 1 to March 31, 2018, as the reference standard to confirm HBV and HCV infection cases. We calculated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) to assess the performance of HBV infection-specific ICD-10-CM codes (B180, B181, and B191) and HCV infection-specific ICD-10-CM codes (B182 and B192) recorded in the NHI Outpatient Claims Dataset to identify patients with HBV or HCV infection. RESULTS: In total, 196,635 and 120,628 patients had analyzable results for HBsAg/HBeAg tests and anti-HCV tests, respectively. Moreover, 44,574 and 14,443 were confirmed to have HBV and HCV infection, respectively. The sensitivity, specificity, PPV, and NPV were, respectively, 46%, 83%, 45%, and 84% for HBV infection-specific ICD-10-CM codes and 47%, 99%, 81%, and 93% for HCV infection-specific ICD-10-CM codes. The sensitivity demonstrated great variation by region, clinical setting, and physician specialty. CONCLUSION: The HBV and HCV infection-specific ICD-10-CM codes recorded by physicians in Taiwan NHI outpatient claims data in 2018 had moderate sensitivity and high specificity for both HBV and HCV infection. The PPV was high for HCV ICD-10-CM codes, yet moderate for HBV ICD-10-CM codes.

When high-volume PCI operators in high-volume hospitals move to lower volume hospitals-Do they still maintain high volume and quality of outcomes?

OBJECTIVES: The aim of this quasi-experimental study was to examine whether high-volume percutaneous coronary intervention (PCI) operators still maintain high volume and quality of outcomes when they moved to lower volume hospitals. BACKGROUND: Systematic reviews have indicated that high-volume PCI operators and hospitals have higher quality outcomes. However, little is known on whether high PCI volume and high quality outcomes are mainly due to operator characteristics (i.e., skill and experience) and is portable across organizations or whether it is due to hospital characteristics (i.e., equipment, team, and management system) and is less portable. METHODS: We used Taiwan National Health Insurance claims data 2000-2012 to identify 98 high-volume PCI operators, 10 of whom moved from one hospital to another during the study period. We compared the PCI volume, risk-adjusted mortality ratio, and major adverse cardiovascular event (MACE) ratio before and after moving. RESULTS: Of the 10 high-volume operators who moved, 6 moved from high- to moderate- or low-volume hospitals, with median annual PCI volumes (interquartile range) of 130 (117-165) in prior hospitals and 54 (46-84) in subsequent hospitals (the hospital the operator moved to), and the remaining 4 moved from high to high-volume hospitals, with median annual PCI volumes (interquartile range) of 151 (133-162) in prior hospitals and 193 (178-239) in subsequent hospitals. No significant differences were observed in the risk-adjusted mortality ratios and MACE ratios between high-volume operators and matched controls before and after moving. CONCLUSIONS: High-volume operators cannot maintain high volume when they moved from high to moderate or low-volume hospitals; however, the quality of care is maintained. High PCI volume and high-quality outcomes are less portable and more hospital bound.

Conceptual-driven classification for coding advise in health insurance reimbursement.

OBJECTIVE: With the non-stop increases in medical treatment fees, the economic survival of a hospital in Taiwan relies on the reimbursements received from the Bureau of National Health Insurance, which in turn depend on the accuracy and completeness of the content of the discharge summaries as well as the correctness of their International Classification of Diseases (ICD) codes. The purpose of this research is to enforce the entire disease classification framework by supporting disease classification specialists in the coding process. METHODOLOGY: This study developed an ICD code advisory system (ICD-AS) that performed knowledge discovery from discharge summaries and suggested ICD codes. Natural language processing and information retrieval techniques based on Zipf's Law were applied to process the content of discharge summaries, and fuzzy formal concept analysis was used to analyze and represent the relationships between the medical terms identified by MeSH. In addition, a certainty factor used as reference during the coding process was calculated to account for uncertainty and strengthen the credibility of the outcome. RESULTS: Two sets of 360 and 2579 textual discharge summaries of patients suffering from cerebrovascular disease was processed to build up ICD-AS and to evaluate the prediction performance. A number of experiments were conducted to investigate the impact of system parameters on accuracy and compare the proposed model to traditional classification techniques including linear-kernel support vector machines. The comparison results showed that the proposed system achieves the better overall performance in terms of several measures. In addition, some useful implication rules were obtained, which improve comprehension of the field of cerebrovascular disease and give insights to the relationships between relevant medical terms. CONCLUSION: Our system contributes valuable guidance to disease classification specialists in the process of coding discharge summaries, which consequently brings benefits in aspects of patient, hospital, and healthcare system.

A stochastic HMM-based forecasting model for fuzzy time series.

Recently, fuzzy time series have attracted more academic attention than traditional time series due to their capability of dealing with the uncertainty and vagueness inherent in the data collected. The formulation of fuzzy relations is one of the key issues affecting forecasting results. Most of the present works adopt IF-THEN rules for relationship representation, which leads to higher computational overhead and rule redundancy. Sullivan and Woodall proposed a Markov-based formulation and a forecasting model to reduce computational overhead; however, its applicability is limited to handling one-factor problems. In this paper, we propose a novel forecasting model based on the hidden Markov model by enhancing Sullivan and Woodall's work to allow handling of two-factor forecasting problems. Moreover, in order to make the nature of conjecture and randomness of forecasting more realistic, the Monte Carlo method is adopted to estimate the outcome. To test the effectiveness of the resulting stochastic model, we conduct two experiments and compare the results with those from other models. The first experiment consists of forecasting the daily average temperature and cloud density in Taipei, Taiwan, and the second experiment is based on the Taiwan Weighted Stock Index by forecasting the exchange rate of the New Taiwan dollar against the U.S. dollar. In addition to improving forecasting accuracy, the proposed model adheres to the central limit theorem, and thus, the result statistically approximates to the real mean of the target value being forecast.