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1.
Future Healthc J ; 11(1): 100127, 2024 Mar.
Article in English | MEDLINE | ID: mdl-38689701

ABSTRACT

The allocation of healthcare resources is reliant upon accurate information generated through clinical coding. Several factors contribute to coding inaccuracies, one of which is interpreting medical documentation. A lack of awareness among medical staff of the clinical coding process and the importance of detailed documentation exacerbates this problem. To investigate this further, 1 month of inpatient clinical coding data from a single hospital ward was reviewed by clinicians experienced in the coding and auditing process. If the reviewing clinician identified inaccuracies in the initial clinical coding, Healthcare Resource Group (HRG) codes were changed. Education sessions were then provided both to junior clinicians working on the hospital ward and to clinical coding staff and a further month of clinical coding data was again reviewed to assess for any difference after the sessions. HRG changes were made in 58.5% of 94 cases initially. Following the educational sessions, 20.5% of HRGs changed in 73 cases (p<0.0001), indicating more accurate initial clinical coding. There were also statistically significant reductions in the extent to which the primary and secondary diagnoses were changed. This study demonstrates that targeted education sessions for both junior clinicians and clinical coding staff can improve the accuracy of inpatient clinical coding.

4.
3 Biotech ; 10(10): 458, 2020 Oct.
Article in English | MEDLINE | ID: mdl-33088655

ABSTRACT

Co-occurrence of two devastating foliar-fungal diseases of peanut, viz., late leaf spot (LLS), and rust may cause heavy yield loss besides adversely affecting the quality of kernel and fodder. This study reports the mapping of seven novel stress-related candidate EST-SSRs in a region having major QTLs for LLS and rust diseases using an F2 mapping population (GJG17 × GPBD4) consisting of 328 individuals. The parental polymorphism using 1311 SSRs revealed 84 SSRs (6.4%) as polymorphic and of these 70 SSRs could be mapped on 14 linkage groups (LG). QTL analysis has identified a common QTL (LLSQTL1/RustQTL) for LLS and rust diseases in the map interval of 1.41 cM on A03 chromosome, explaining 47.45% and 70.52% phenotypic variations, respectively. Another major QTL for LLS (LLSQTL1), explaining a 29.06% phenotypic variation was also found on LG_A03. A major rust QTL has been validated which was found harboring R-gene and resistance-related genes having a role in inducing hypersensitive response (HR). Further, 23 linked SSRs including seven novel EST-SSRs were also validated in 177 diverse Indian groundnut genotypes. Twelve genotypes resistant to both LLS and rust were found carrying the common (rust and LLS) QTL region, LLS QTL region, and surrounding regions. These identified and validated candidate EST-SSR markers would be of great use for the peanut breeding groups working for the improvement of foliar-fungal disease resistance.

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