The effect of quality improvement interventions on inpatient cancer malnutrition documentation and coding in an academic medical center.

38 Background: Malnutrition (MN) is common yet underdiagnosed in hospitalized cancer patients. Effective assessments can identify those who need nutritional care and help plan intervention. We examined the effect of quality improvement (QI) interventions on the dietitian documented MN (DDMN) and physician coded malnutrition (PCMN). We also determined if the registered dietitian (RD) and physician assessments of MN agreed. Methods: Electronic medical records (EMR) were reviewed for a consecutive cohort of inpatients with a solid tumor diagnosis staged I-IV and admitted to Atrium Health’s Carolinas Medical Center at least once between 1/1/2016 to 5/31/2019. Data were collected from the first admission EMR encounter closest to the cancer diagnosis date. RD assessments were reviewed for DDMN. PCMN diagnosis was based on MN ICD-10 codes in the discharge summary. MN was graded as mild, moderate, and severe. Two QI interventions were implemented during the study period: 1) 8/2016: RD message via EMR to query MD approval for MN diagnosis; 2) 4/2018: Clinical Documentation Integrity Team query MD by sending ASPEN criteria via an alert integrated into MD workflow. Agreement in MN identification was defined as the absence or presence of both DDMN and PCMN; agreement in severity was defined as the absence of DDMN and PCMN or the agreement in presence and severity of DDMN and PCMN. Cochran-Armitage tests for trend assessed prevalence and agreement across the three periods (N1=652; N2=2858; N3=1622) defined by the two sequential QI interventions. Results: N=5143; 52% males. Median age 63 (range 18-102) years. 70% White; 24% Black, 3% Latino. Commonest cancer diagnostic groups: Upper Gastrointestinal 22%, Thoracic (19%), Genitourinary 18%. 28% had stage IV disease. 11% (N=557) met criteria for DDMN and/or PCMN. Of the 557, 40% (N=223) met criteria for both DDMN and PCMN. DDMN (N=420) was mild 2%, moderate 19%, and severe 79%. On discharge, PCMN (N=360) was mild in 10%, moderate in 21%, and severe in 69%. The RD and MD agreed on the presence or absence (94%) and severity (93%) of MN. Significant trends were observed as DDMN prevalence increased from 3.1%, 8.1%, to 10.3% (p<.001), and PCMN prevalence from 0.5%, 7.8%, to 8.2% (p<.001). While rates of mild, moderate, and severe MN varied across the periods, statistically significant change in these distributions was not identified in DDMN (p=0.62) or PCMN (p=0.20) after the second QI intervention. Conclusions: MN was under-diagnosed compared to nutrition intervention studies. When MN was identified, it was moderate or severe in the majority. Evaluations by RD and MD were highly congruent for MN prevalence and severity. Implementation of nutrition-focused QI interventions improved documentation and coding of MN. Improved communication between the RD and the MD could improve the recognition and diagnosis of MN.

Suitability of Papanicolaou stain for micronuclei mass screening in buccal smears comparing reference feulgen stain and papanicolaou stain in field

<strong>Background:</strong> Micronuclei (MN) assessment so far was done directly, individually, and intra- and, here, inter-observer bias could not be eliminated. It was subjective. <strong>Methods:</strong> In this study, accurate and reproducible MN counting was facilitated by the use of liquid cytology and image capturing with MN identification analysis. <strong>Results:</strong> Comparing the two nuclear staining techniques - DNA specific Feulgen stain and commonly available Papanicolaou (PAP) stain we found that both techniques gave statistically comparable accurate and reproducible MN results. T-test and non-parametric followed by paired non-parametric and then Wilcoxon matched-pairs signed rank test tell us that both the staining procedures have no difference at P &lt;0.05. <strong>Conclusion:</strong> These protocols are comparable and reproducible, and may be adoptable for mass screening to assess the genotoxic effects of substances like tobacco.