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Assessment of clinical workload for general and specialty genetic counsellors at an academic medical center: a tool for evaluating genetic counselling practices
With genomics influencing clinical decisions, genetics professionals are exponentially called upon as part of multidisciplinary care. Increasing demand for genetic counselling, a limited workforce, necessitates practices improve efficiency. We hypothesised that distinct differences in clinical workl...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5685297/ https://www.ncbi.nlm.nih.gov/pubmed/29263811 http://dx.doi.org/10.1038/npjgenmed.2016.10 |
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author | Heald, Brandie Rybicki, Lisa Clements, Diane Marquard, Jessica Mester, Jessica Noss, Ryan Nardini, Monica Polk, Jill Psensky, Brittany Rigelsky, Christina Schreiber, Allison Shealy, Amy Smith, Marissa Eng, Charis |
author_facet | Heald, Brandie Rybicki, Lisa Clements, Diane Marquard, Jessica Mester, Jessica Noss, Ryan Nardini, Monica Polk, Jill Psensky, Brittany Rigelsky, Christina Schreiber, Allison Shealy, Amy Smith, Marissa Eng, Charis |
author_sort | Heald, Brandie |
collection | PubMed |
description | With genomics influencing clinical decisions, genetics professionals are exponentially called upon as part of multidisciplinary care. Increasing demand for genetic counselling, a limited workforce, necessitates practices improve efficiency. We hypothesised that distinct differences in clinical workload exist between various disciplines of genetic counselling, complicating practice standardisation and patient volume expectations. We thus sought to objectively define and assess workload among various specialties of genetic counselling. Twelve genetic counsellors (GCs), representing 9.3 clinical FTE, in general or specialty (cancer, cardiovascular or prenatal) services at an academic health system developed a data collection tool for assessing time and complexity. Over a 6-week period, the data were recorded for 583 patient visits (136 general and 447 specialty) and analysed comparing general versus specialty GCs. Variables were compared with hierarchical linear models for ordinal or continuous data and hierarchical logistic models for binary data. General GCs completed more pre- and post-visit activities (P=0.011) and spent more time (P=0.009) per case. General GCs reported greater case discussion with other providers (P<0.001), literature review (P=0.026), exploring testing options (P=0.041), electronic medical record review (P=0.040), insurance preauthorization (P=0.05) and fielding patient inquiries (P=0.003). Lesser redundancy in referral indication was observed by general GCs. GCs in general practice carry a higher pre- and post-visit workload compared with GCs in specialty practices. General GCs may require lower patient volumes than specialty GCs to allow time for additional pre- and post-visit activities. Non-clinical activities should be transferred to support staff. |
format | Online Article Text |
id | pubmed-5685297 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-56852972017-12-20 Assessment of clinical workload for general and specialty genetic counsellors at an academic medical center: a tool for evaluating genetic counselling practices Heald, Brandie Rybicki, Lisa Clements, Diane Marquard, Jessica Mester, Jessica Noss, Ryan Nardini, Monica Polk, Jill Psensky, Brittany Rigelsky, Christina Schreiber, Allison Shealy, Amy Smith, Marissa Eng, Charis NPJ Genom Med Article With genomics influencing clinical decisions, genetics professionals are exponentially called upon as part of multidisciplinary care. Increasing demand for genetic counselling, a limited workforce, necessitates practices improve efficiency. We hypothesised that distinct differences in clinical workload exist between various disciplines of genetic counselling, complicating practice standardisation and patient volume expectations. We thus sought to objectively define and assess workload among various specialties of genetic counselling. Twelve genetic counsellors (GCs), representing 9.3 clinical FTE, in general or specialty (cancer, cardiovascular or prenatal) services at an academic health system developed a data collection tool for assessing time and complexity. Over a 6-week period, the data were recorded for 583 patient visits (136 general and 447 specialty) and analysed comparing general versus specialty GCs. Variables were compared with hierarchical linear models for ordinal or continuous data and hierarchical logistic models for binary data. General GCs completed more pre- and post-visit activities (P=0.011) and spent more time (P=0.009) per case. General GCs reported greater case discussion with other providers (P<0.001), literature review (P=0.026), exploring testing options (P=0.041), electronic medical record review (P=0.040), insurance preauthorization (P=0.05) and fielding patient inquiries (P=0.003). Lesser redundancy in referral indication was observed by general GCs. GCs in general practice carry a higher pre- and post-visit workload compared with GCs in specialty practices. General GCs may require lower patient volumes than specialty GCs to allow time for additional pre- and post-visit activities. Non-clinical activities should be transferred to support staff. Nature Publishing Group 2016-05-11 /pmc/articles/PMC5685297/ /pubmed/29263811 http://dx.doi.org/10.1038/npjgenmed.2016.10 Text en Copyright © 2016 Center of Excellence in Genomic Medicine Research/Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Heald, Brandie Rybicki, Lisa Clements, Diane Marquard, Jessica Mester, Jessica Noss, Ryan Nardini, Monica Polk, Jill Psensky, Brittany Rigelsky, Christina Schreiber, Allison Shealy, Amy Smith, Marissa Eng, Charis Assessment of clinical workload for general and specialty genetic counsellors at an academic medical center: a tool for evaluating genetic counselling practices |
title | Assessment of clinical workload for general and specialty genetic counsellors at an academic medical center: a tool for evaluating genetic counselling practices |
title_full | Assessment of clinical workload for general and specialty genetic counsellors at an academic medical center: a tool for evaluating genetic counselling practices |
title_fullStr | Assessment of clinical workload for general and specialty genetic counsellors at an academic medical center: a tool for evaluating genetic counselling practices |
title_full_unstemmed | Assessment of clinical workload for general and specialty genetic counsellors at an academic medical center: a tool for evaluating genetic counselling practices |
title_short | Assessment of clinical workload for general and specialty genetic counsellors at an academic medical center: a tool for evaluating genetic counselling practices |
title_sort | assessment of clinical workload for general and specialty genetic counsellors at an academic medical center: a tool for evaluating genetic counselling practices |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5685297/ https://www.ncbi.nlm.nih.gov/pubmed/29263811 http://dx.doi.org/10.1038/npjgenmed.2016.10 |
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