Channel estimation techniques for Multiple-input Multiple-output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) based on comb type pilot arrangement with least-square error (LSE) estimator was investigated with space-time-frequency (STF) diversity implementation. The frequency offset in OFDM impacts its performance. This was mitigated with the implementation of the presented inter-carrier interference self-cancellation (ICI-SC) techniques and different space-time subcarrier mapping. STF block coding in the system exploits the spatial, temporal and frequency diversity to improve performance. Estimated channel was fed into a decoder which combines the STF decoding together with the estimated channel coefficients using LSE estimator for equalization. The performance of the system is compared by measuring the symbol error rate with a PSK-16 and PSK-32. The results show that subcarrier mapping together with ICI-SC were able to increase the system performance. Introduction of channel estimation was also able to estimate the channel coefficient at only 5dB difference with a perfectly known channel.
The objective of this study was to optimise the extraction conditions for phenolic compounds from limau purut (Citrus hystrix) peels using response surface methodology (RSM). A central composite rotatable design (CCRD) was applied to determine the effects of ethanol concentration (%), extraction temperature (oC), and extraction time (min) on total phenolic content (TPC) from limau purut (Citrus hystrix) peels. The independent variables were coded at five levels and their actual values were selected based on the results of single factor experiments. Results showed that ethanol concentration was the most significant (p
BACKGROUND: The accuracy of clinical coding is crucial in the assignment of Diagnosis Related Groups (DRGs) codes, especially if the hospital is using Casemix System as a tool for resource allocations and efficiency monitoring. The aim of this study was to estimate the potential loss of income due to an error in clinical coding during the implementation of the Malaysia Diagnosis Related Group (MY-DRG®) Casemix System in a teaching hospital in Malaysia.
METHODS: Four hundred and sixty-four (464) coded medical records were selected, re-examined and re-coded by an independent senior coder (ISC). This ISC re-examined and re-coded the error code that was originally entered by the hospital coders. The pre- and post-coding results were compared, and if there was any disagreement, the codes by the ISC were considered the accurate codes. The cases were then re-grouped using a MY-DRG® grouper to assess and compare the changes in the DRG assignment and the hospital tariff assignment. The outcomes were then verified by a casemix expert.
RESULTS: Coding errors were found in 89.4% (415/424) of the selected patient medical records. Coding errors in secondary diagnoses were the highest, at 81.3% (377/464), followed by secondary procedures at 58.2% (270/464), principal procedures of 50.9% (236/464) and primary diagnoses at 49.8% (231/464), respectively. The coding errors resulted in the assignment of different MY-DRG® codes in 74.0% (307/415) of the cases. From this result, 52.1% (160/307) of the cases had a lower assigned hospital tariff. In total, the potential loss of income due to changes in the assignment of the MY-DRG® code was RM654,303.91.
CONCLUSIONS: The quality of coding is a crucial aspect in implementing casemix systems. Intensive re-training and the close monitoring of coder performance in the hospital should be performed to prevent the potential loss of hospital income.
Mortality estimates are important parameters for health monitoring and are routinely used as evidence for health policy and planning. This study aimed to estimate the mortality component of Burden of Disease in Malaysia in 2008. The 2008 mortality data from the Statistics Department were used to estimate cause-specific mortality (by age and sex) in Malaysia. Data were coded using the ICD10 (International Classification of Disease) coding. Calculation of mortality component of Burden of Disease (ie: Years of Life Lost (YLL) was done using the standard Global Burden of Disease Methodology. The total estimated deaths in Malaysia in 2008 were 124,857, of which 72,202 (57.8%) were males. The total years of life lost (YLL) for the Malaysian population in 2008 was 1.51 million in which 0.92 million (60.7%) was among males. Almost three quarter (68%) of the burden of premature deaths resulted from non-communicable diseases, followed by communicable diseases (20%) and injury (12%). Among the top three leading causes of YLL were ischaemic heart disease (17.1%), stroke (9.6%) and road traffic injuries (8.3%). In Malaysia, premature mortality mainly contributed by non-communicable diseases followed by communicable diseases and injury. A multi-agency collaboration is needed to prevent premature death and to improve quality of life.
Background: Database on hospital records like discharge data, birth and death certificates are widely used for epidemiological and research studies. However there are a very few validation studies on these data. The aim of this study was to validate and assess the accuracy of the ICD 10 database on congenital anomalies in the state of Penang. This study was carried out for three years, from 2002 to 2004.
Methods: The list of cases coded under the general coding “Q” was extracted and approximately 30% of cases were randomly selected from the list. Medical records for the selected cases were checked and discrepancies for the diagnoses between the medical records and the ICD 10 data base were recorded for three years. Verification was done for basic demographic variables and the coding of the diseases. Discrepancies, sensitivity and specificity were calculated.
Results: The ICD 10 database for congenital anomalies are classified into two types: Type 1 and Type 2. Discrepancies on demographic information were found among the age of patients (babies with congenital anomalies). In Type 1, there was a discrepancy of about 0.02 % to 0.05% probability that a congenital anomaly case can be recorded as non congenital anomaly in the ICD 10. In Type 2 there was a discrepancy that a non-congenital anomaly was classified as congenital anomaly and this ranged from 26.7% to 50.0%. The sensitivity ranged from 96.85% to 97.98%, thus it can be concluded the ICD 10 database is highly sensitive while the specificity ranged from 50.00% to 78.57 %. In other words the ICD 10 is not accurate when classifying the non- congenital anomaly cases. A fair percentage of non-congenital anomaly cases were classified as CA in the ICD 10 database.
Conclusion: Even though hospital databases are used as a baseline data for a number of research and epidemiological studies it cannot be used at face value. Validation of these data is necessary before any conclusions can be drawn or intervention measures are undertaken.
Purpose The purpose of this paper is to assess National Medical Care Survey data quality. Design/methodology/approach Data completeness and representativeness were computed for all observations while other data quality measures were assessed using a 10 per cent sample from the National Medical Care Survey database; i.e., 12,569 primary care records from 189 public and private practices were included in the analysis. Findings Data field completion ranged from 69 to 100 per cent. Error rates for data transfer from paper to web-based application varied between 0.5 and 6.1 per cent. Error rates arising from diagnosis and clinical process coding were higher than medication coding. Data fields that involved free text entry were more prone to errors than those involving selection from menus. The authors found that completeness, accuracy, coding reliability and representativeness were generally good, while data timeliness needs to be improved. Research limitations/implications Only data entered into a web-based application were examined. Data omissions and errors in the original questionnaires were not covered. Practical implications Results from this study provided informative and practicable approaches to improve primary health care data completeness and accuracy especially in developing nations where resources are limited. Originality/value Primary care data quality studies in developing nations are limited. Understanding errors and missing data enables researchers and health service administrators to prevent quality-related problems in primary care data.
Understanding the normal anatomical features as well as the more unusual developmental anomalies of teeth, roots and root canals is essential for successful root canal treatment. In addition to various types of root canal configuration and accessory canal morphology, a wide range of developmental tooth, root and canal anomalies exists, including C-shaped canals, dens invaginatus, taurodontism, root fusion, dilacerations and palato-gingival grooves. There is a direct association between developmental anomalies and pulp and periradicular diseases that usually require a multidisciplinary treatment approach to achieve a successful outcome. A number of classifications have categorized tooth, root and canal anomalies; however, several important details are often missed making the classifications less than ideal and potentially confusing. Recently, a new coding system for classifying root, root canal and accessory canal morphology has been introduced. The purpose of this article is to introduce a new system for classifying tooth, root and canal anomalies for use in research, clinical practice and training, which can serve as complementary codes to the recently described system for classifying root, as well as main and accessory canal morphology.