Dependability of Nursing Informatics System CHAPTER 17

Total Page:16

File Type:pdf, Size:1020Kb

Dependability of Nursing Informatics System CHAPTER 17 CHAPTER 16 – Dependability of Nursing Informatics System CHAPTER 17- Nursing Minimum Data Set CHAPTER 18- Theories Models and Frameworks SUBMITTED BY: Cabanalan, Romar C. Ladjarani, Sandra H. Maulana, Dayang Almira H. Sharif Masdal, Sarah P. Musa, Shiedjian A. BSN-IIB SUBMITTED TO: Mr. Roderick P. Go Nursing Informatics Professor DATE SUBMITTED: May 10, 2013 CHAPTER 16 Dependability of Nursing Informatics System Dependable System is the measure of the reliability, integrity and performance of the system. It is defines as trustworthiness of a computing system which allows reliance to be justifiably placed on the service it delivers. It is the collective term used to describe the availability performance and its influencing factors: reliability performance, maintainability performance and maintenance support performance. In nursing informatics, dependability is the measure of the effectiveness of the health care delivery, quality of service and quality of care through the use of health information system. It encompasses the reliability, integrity, confidentiality and security of the data, information and the process. Factors that affects dependability of systems A. Error In the health care information system, it is the discrepancy between actual results and behavior from the expected or the reference condition or expected performance. In hospitals and clinics, data error or inaccuracy of the information is resulted when an incorrect reading is registered in the measuring equipment, the measuring device is malfunctioning unnoticeably, mishandling of data, incorrect reading of data (honest mistake), the computer system does not properly process the data, a potential bug is existing in the program, the data process by the computer program overflows, incorrect processing of tables and indexes, etc. Hour Systolic Diastolic H-01 140 110 H-02 145 110 H-03 140 115 H-04 140 110 H-05 135 100 H-06 140 95 H-07 135 95 H-08 135 100 H-09 130 105 H-10 140 110 H-11 110 160 H-12 135 100 H-13 140 100 H-14 145 100 H-15 145 95 Based on the historical pattern, systolic reading is greater than diastolic reading. A diastolic reading of 160 mmHg which is more than the systolic reading of 110 mmHg is an indication that there is an error in reading the data. B. Fault Sometimes due to computer bug which is considered a defect in the system. The presence of a fault in health information system may or may not lead to a failure BSA (m ) Height (cm) Weight (kg) 1.45484 152 50 1.88569 213 60 0.76000 180 52 1.68762 117 58 160006 165 56 1..1276 162 51 1.49276 171 47 Converting the table into chart, we can evidently see that there is an error in the results. Based on our knowledge, if the height and/or weight is increase there is corresponding increase in the body surface area (BSA), on the contrary, point number 14 of the figure shown below, gives an opposite results. We can say that is an error in processing the data and not the inputting of the data, since the height and weight is correct. C. Failure It is a condition in which the system performs unnecessarily or the function is contrary to its specification or the expected condition. An error may not necessarily cause a failure; however a persistent fault can have an impact that mitigates a failure condition. Example is a problem in the network occurs resulting to unavailability of the communication system. This common problem should be anticipated; as such preventive measures and contingency plan should be incorporated in the planning and implementation of the health information. CHAPTER 17 Nursing Minimum Data Set Health Information technology offers a large number of benefits to the nurses and healthcare providers as well as the patients and consumers such as the quality and effectiveness of healthcare delivery and service. Migration from the paper-based to electronic/computer health records minimizes irregularities in the workflow process and decision making process. To accurately and consistently document, accumulate, combined, translate, and retrieve health information data, fields, data set, and data elements must have an equivalent vocabularies and/ or terminologies within the healthcare record before it stores in the database. The Nursing Minimum Data Set (NMDS) provides a formal structure for electronic healthcare data elements and components to support nursing care in all settings. What is Minimum Data Set? The minimum data set providers the specific reference information for the user such as the drug uses, dosage requirement, and direction for use, active ingredients, dates, and other relevant information. The Nursing Minimum Data Set/Elements The Nursing Minimum Data Set (NMDS) is categorization scheme for the standardization of collection, integration, storage, classification, retrieval and reporting of essential nursing data. The collected data will essentially provide an accurate description of nursing decision, nursing diagnose, nursing care, nursing resources, nursing services, etc. used when providing patient care. The Nursing Minimum Data Set endeavors the standardization of the aggregated of essential nursing data. Drug Fact Active Ingredients Purpose Uses Warnings Directions Other Information Inactive Ingredients Other Information Questions/ Comments? The Nursing Minimum Data Set (NMDS) encompasses three categorical scheme or elements which includes the following: Nursing Care Elements Nursing Diagnosis Nursing Intervention Nursing Outcome Nursing Care Intensity Patient Demographic Elements Personal Identification Date of Birth Sex Nationality Residence Service Elements Unique facility or agency number elements Unique patient health record number Unique number of principle Registered Nurse Episode admission Discharge or termination date Disposition of patient Expected payer for medical bill CHAPTER 18 Theories Models and Frameworks Informatics System in Health Care Industry Information system is collective term referring to a system of data records and activities that processes and translate the data to information in an automated process. The processing of data involves the use of computer systems and specialized software that manipulates the information- processing activities of the organization. Computer- based information systems are in the field of information technology. Thus, the discipline of nursing informatics is related to the processing of the data of patients records into information which are supported by information systems. Information Systems in the Hospital Transaction processing Information System Operation System Individual Patient record Hospital Information System Nursing Information System Pharmacy Health System Preservation of Healthcare Quality Theory in Nursing Informatics In the Philippines, many organizations such as Department Of Health are trying to educate and inform the public about health care quality. The purpose of implementing quality health care is to offer expert advice and suggest noteworthy approaches to solve medical problems, illnesses, sickness, ailment, disorder and complaints. Notwithstanding the readiness of the solution, the solution typically involves a multitude of strategies including regulatory forms, financial incentives, independent oversight and patient education. HEALTH INFORMATION TECHNOLOGY (HIT) Article 8 section 11 of the 1987 constitution of the Philippines States the “the state shall adopt an integrated and comprehensive approach to health development which small endeavor to make essential goods, health and other social services available to all people.” Health Informatics Paradigm Shift Basic Steps to properly implement the nursing information system in the Hospital: Stage 1 3 Translate Data into Information (with 2 statistical Collecting and 1 Analyzing the Data Commencing the Project STAGE 2 health care provider are provided simultaneously. 6 Project Evaluation 5 Support from the Client 4 Dissemination of Information .
Recommended publications
  • A Methodology for Developing a Nursing Education Minimum Dataset Aziza A
    University of South Florida Scholar Commons Graduate Theses and Dissertations Graduate School 11-10-2005 A Methodology for Developing a Nursing Education Minimum Dataset Aziza A. Rajab University of South Florida Follow this and additional works at: https://scholarcommons.usf.edu/etd Part of the American Studies Commons Scholar Commons Citation Rajab, Aziza A., "A Methodology for Developing a Nursing Education Minimum Dataset" (2005). Graduate Theses and Dissertations. https://scholarcommons.usf.edu/etd/826 This Dissertation is brought to you for free and open access by the Graduate School at Scholar Commons. It has been accepted for inclusion in Graduate Theses and Dissertations by an authorized administrator of Scholar Commons. For more information, please contact [email protected]. A Methodology for Developing a Nursing Education Minimum Dataset by Aziza A. Rajab A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy College of Nursing University of South Florida Major Professor: Mary E. Evans, Ph.D. Patricia Burns, Ph.D. Arthur Shapiro, Ph.D. Jason Beckstead, Ph.D. Date of Approval: November 10, 2005 Keywords: coding scheme, classification systems, Delphi, focus group, nursing database, nursing data element, nursing education, online survey, ontology, taxonomy, unified nursing language © Copyright 2005, Aziza A. Rajab Acknowledgments Thanks goes first to God Almighty, Allah the most merciful, compassionate, and gracious, for granting me the health and ability to conduct this study. A very special thank you goes to my advisor, chair, and Associate Dean for Research & Doctoral Study in the College of Nursing, Dr. Mary E. Evans for her guidance, supervision, and instruction throughout my doctoral studies and this research.
    [Show full text]
  • Key Performance Indicators a Guide to Choosing, Developing and Using Kpis for Clinical Nurse/Midwife Specialists and Advanced Nurse/Midwife Practitioners
    DISCUSSION PAPER 3 Key Performance Indicators A Guide to Choosing, Developing and Using KPIs for Clinical Nurse/Midwife Specialists and Advanced Nurse/Midwife Practitioners DECEMBER 2010 KEY PERFORMANCE INDICATORS Introduction Development of healthcare in Ireland, including its structures and delivery of care, is driven by the safety and quality agenda that has become increasingly explicit in the last ten years (Department of Health and Children 2008). Nurses and midwives have contributed and continue to contribute to the enhancement of patient care and this contribution can be captured and articulated by focusing on their clinical outcomes. The National Council for the Professional Development of Nursing and Midwifery has provided focused guidance on measuring clinical outcomes in its discussion paper Clinical Outcomes (National Council 2010a). Building on that guidance, the present discussion paper has been developed as a resource for clinical nurse/midwife specialists (CNSs/CMSs) and advanced nurse/midwife practitioners (ANPs/AMPs) wishing to articulate and clarify their contribution to patient care. The need for this specialised guidance emerged from a recent evaluation of CNSs’/CMSs’ and ANPs’/AMPs’ clinical outcomes, and the final report on the evaluation contains a recommendation concerning the development of key performance indicators relevant to the roles of these nurses and midwives. The Evaluation of Clinical Nurse/Midwife Specialists and Advanced Nurse/Midwife Practitioners in Ireland Known as the SCAPE Project, the examination of CNSs’/CMSs’ and ANPs’/AMPs’ clinical outcomes involved the use of an extensive variety of research methods and date collection tools (Begley et al 2010). The study demonstrated that patient care provided by CNSs/CMSs and ANPs/AMPs improved patient outcomes, as well as being safe and cost-neutral.
    [Show full text]
  • Letter from ANA to the Office of National Coordinator for Health IT
    November 6, 2015 Karen DeSalvo, MD, MPH, MSc National Coordinator Office of National Coordinator for Health IT Department of Health and Human Services 200 Independence Ave, SW Washington, DC 20201 Re: Comments on 2016 Interoperability Standards Advisory Best Available Standards and Implementation Specifications Submitted via: https://www.healthit.gov/standards-advisory/2016 Dear Dr. DeSalvo: The American Nurses Association (ANA) welcomes the opportunity to provide comments on the document “2016 Interoperability Standards Advisory Best Available Standards and Implementation Specifications.” As the only full-service professional organization representing the interests of the nation’s 3.4 million registered nurses (RNs), ANA is privileged to speak on behalf of its state and constituent member associations, organizational affiliates, and individual members. RNs serve in multiple direct care, care coordination, and administrative leadership roles, across the full spectrum of health care settings. RNs provide and coordinate patient care, educate patients, their families and other caregivers as well as the public about various health conditions, wellness, and prevention, and provide advice and emotional support to patients and their family members. ANA members also include the four advanced practice registered nurse (APRN) roles: nurse practitioners, clinical nurse specialists, certified nurse-midwives and certified registered nurse anesthetists.1 We appreciate the efforts of the Office of the National Coordinator for Health Information Technology
    [Show full text]
  • American Psychological Association 5Th Edition
    NURSING DIAGNOSES IN THE CARE OF HOSPITALIZED PATIENTS WITH TYPE 2 DIABETES MELLITUS: PATTERN ANALYSIS AND CORRELATES OF HEALTH DISPARITIES Kennedy O. Onori A dissertation submitted to the faculty of the University of North Carolina at Chapel Hill in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the School of Nursing. Chapel Hill 2013 Approved by: _ Edward J. Halloran, PhD, RN, FAAN Lorna H. Harris, PhD, RN, FAAN Allison A. Vorderstrasse, DNSc, RN Shielda G. Rodgers, PhD, RN Jamie L. Crandell, PhD © 2013 Kennedy O. Onori ALL RIGHTS RESERVED ii ABSTRACT KENNEDY O. ONORI: Nursing Diagnoses in the Care of the Hospitalized Patient with Type 2 Diabetes Mellitus: Pattern Analysis and Correlates of Health Disparities (Under the direction of Edward J. Halloran, RN, PhD, FAAN) This study examined the human needs of 445 adults admitted to hospital with the primary medical diagnosis of Type 2 Diabetes Mellitus [ICD-9CM 250.0-9] and compared the pattern of nursing diagnoses (human needs) with those of 5321 patients having Type 2 DM but admitted to hospital for other reasons and with the 78,480 inpatients with no DM. Length of hospital stay, intensive care unit use and discharge dispositions were examined, controlling for race, poverty, marital status and age, to determine if the nursing diagnosis variables were distinctive for any of the three patient groups. A subset of 14 nursing diagnoses was identified from the literature on the care of Type 2 DM to determine how they varied among the three groups. The 61 nursing diagnoses were also fitted in regression models to explain variances in patient length of stay and to explore patient diabetes status.
    [Show full text]
  • The Benefits of Using Standardized Nursing Terminology
    Page 1 of 20 Selecting a Standardized Terminology for the Electronic Health Record that Reveals the Impact of Nursing on Patient Care By Cynthia B. Lundberg, R.N., BSN; SNOMED Terminology Solutions; Judith J. Warren, PhD, RN, BC, FAAN, FACMI; University of Kansas; Jane Brokel, PhD, RN, NANDA International; Gloria M. Bulechek, PhD, RN, FAAN; Nursing Interventions Classification; Howard K. Butcher, PhD, RN, APRN, BC; Nursing Interventions Classification; Joanne McCloskey Dochterman, PhD, RN, FAAN; Nursing Interventions Classification; Marion Johnson, PhD, RN; Nursing Outcomes Classification; Meridean Maas PhD, RN; Nursing Outcomes Classification; Karen S. Martin, RN, NSN, FAAN; Omaha System; Sue Moorhead PhD, RN, Nursing Outcomes Classification; Christine Spisla, RN, MSN; SNOMED Terminology Solutions; Elizabeth Swanson, PhD, RN; Nursing Outcomes Classification, Sharon Giarrizzo-Wilson, RN, BSN/MS, CNOR, Association of PeriOperative Registered Nurses Citation: Lundberg, C., Warren, J.., Brokel, J., Bulechek, G., Butcher, H., McCloskey Dochterman, J., Johnson, M., Mass, M., Martin, K., Moorhead, S., Spisla, C., Swanson, E., & Giarrizzo-Wilson, S. (June, 2008). Selecting a Standardized Terminology for the Electronic Health Record that Reveals the Impact of Nursing on Patient Care. Online Journal of Nursing Informatics (OJNI), 12, (2). Available at http:ojni.org/12_2/lundberg.pdf Page 2 of 20 Abstract Using standardized terminology within electronic health records is critical for nurses to communicate their impact on patient care to the multidisciplinary team. The universal requirement for quality patient care, internal control, efficiency and cost containment, has made it imperative to express nursing knowledge in a meaningful way that can be shared across disciplines and care settings. The documentation of nursing care, using an electronic health record, demonstrates the impact of nursing care on patient care and validates the significance of nursing practice.
    [Show full text]
  • TELENURSE -Nursing Classifications, Quality Indicators and the Electronic Nursing Record
    Medical Informatics Europe '97 133 C. Pappas et al. (Eds.) IOS Press, 1997 TELENURSE -Nursing Classifications, Quality Indicators and the Electronic Nursing Record Hendrik D. Jorgensen and Tommy M. Nielsen, Kommunedata, The Centre for Health Information Services, Lautrupvang 3, DK-2750 Ballerup, Denmark Abstract. In the area of nursing, national and international clinical databases are practically non-existing. The lack of common nomenclatures and classifications is the main reason for this situation. This article elaborates on the TELENURSE project's two objectives which focus on improving that situation. The first objective concerns the "The International Classification for Nursing Practice" (ICNP) and methods for implementation of ICNP electronically in nursing modules of electronic patient records. The second objective concerns the development of a clinical nursing database in which clinical data collected from electronic nursing systems can be stored. On the basis of this data storage, nursing indicators can be developed, which in the long term allows for comparison of nursing interventions across Europe. 1. Introduction In the nursing community, there is considerable interest in recording nursing activities in a structured manner and in being able to use the structured data for assessment and comparison of the quality of nursing care provided at local, regional, national - and even international - levels. Due to the lack of internationally accepted nomenclatures and classifications, which provide a framework for suitably structuring nursing information, it has until now been very difficult to effectively satisfy this interest. Additionally, the limited use of electronic nursing records by nurses in their daily work makes the provision of structured and standardised nursing data almost impossible.
    [Show full text]
  • Dependability of Nursing Informatics System CHAPTER 17
    CHAPTER 16 – Dependability of Nursing Informatics System CHAPTER 17- Nursing Minimum Data Set CHAPTER 18- Theories Models and Frameworks SUBMITTED BY: Cabanalan, Romar C. Ladjarani, Sandra H. Maulana, Dayang Almira H. Sharif Masdal, Sarah P. Musa, Shiedjian A. BSN-IIB SUBMITTED TO: Mr. Roderick P. Go Nursing Informatics Professor DATE SUBMITTED: May 10, 2013 CHAPTER 16 Dependability of Nursing Informatics System Dependable System is the measure of the reliability, integrity and performance of the system. It is defines as trustworthiness of a computing system which allows reliance to be justifiably placed on the service it delivers. It is the collective term used to describe the availability performance and its influencing factors: reliability performance, maintainability performance and maintenance support performance. In nursing informatics, dependability is the measure of the effectiveness of the health care delivery, quality of service and quality of care through the use of health information system. It encompasses the reliability, integrity, confidentiality and security of the data, information and the process. Factors that affects dependability of systems A. Error In the health care information system, it is the discrepancy between actual results and behavior from the expected or the reference condition or expected performance. In hospitals and clinics, data error or inaccuracy of the information is resulted when an incorrect reading is registered in the measuring equipment, the measuring device is malfunctioning unnoticeably, mishandling of data, incorrect reading of data (honest mistake), the computer system does not properly process the data, a potential bug is existing in the program, the data process by the computer program overflows, incorrect processing of tables and indexes, etc.
    [Show full text]
  • Standard Nursing Terminologies: a Landscape Analysis
    Standard Nursing Terminologies: A Landscape Analysis MBL Technologies, Clinovations, Contract # GS35F0475X Task Order # HHSP2332015004726 May 15, 2017 Table of Contents I. Introduction ....................................................................................................... 4 II. Background ........................................................................................................ 4 III. Landscape Analysis Approach ............................................................................. 6 IV. Summary of Background Data ............................................................................ 7 V. Findings.............................................................................................................. 8 A. Reference Terminologies .....................................................................................................8 1. SNOMED CT ................................................................................................................................... 8 2. Logical Observation Identifiers Names and Codes (LOINC) ........................................................ 10 B. Interface Terminologies .................................................................................................... 11 1. Clinical Care Classification (CCC) System .................................................................................... 11 2. International Classification for Nursing Practice (ICNP) ............................................................. 12 3. NANDA International
    [Show full text]
  • Building Standard-Based Nursing Information Systems
    Building Standard-Based Nursing Information Systems Pan American Health Organization World Health Organization Division of Health Systems and Services Development Essential Drugs and Technology Organization and Management of Health Systems and Services Human Resource Development December 2000 PAHO Library Cataloguing in Publication Data Pan American Health Organization. Building Standard-Based Nursing Information Systems. Washington, D.C. : PAHO, © 2000. 141 p. ISBN 92 75 12364 0 I. Title. 1. INFORMATION SYSTEMS. 2. NURSING. 3. NURSING PRACTICE CLASSIFICATIONS. 4. QUALITY OF HEALTHCARE. 5. MANUALS NLM W26.55.I4.p187 2001 ISBN 92 75 12364 0 The Pan American Health Organization welcomes requests for permission to reproduce or translate its publications, in part or in full. Applications and inquiries should be addressed to the Publications Program, Pan American Health Organization, Washington, D.C., which will be glad to provide the latest information on any changes made to the text, plans for new editions, and reprints and translations already available. © Pan American Health Organization, 2000 Publications of the Pan American Health Organization enjoy copyright protection in accordance with the provisions of Protocol 2 of the Universal Copyright Convention. All rights reserved. The designations employed and the presentation of the material in this publication do not imply the expression of any opinion whatsoever on the part of the Secretariat of the Pan American Health Organization concerning the legal status of any country, territory, city, or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. The mention of specific companies or of certain manufacturers' products does not imply that they are endorsed or recommended by the Pan American Health Organization in preference to others of a similar nature that are not mentioned.
    [Show full text]
  • Abstraction Tool for Standardized, Comparable, Essential Data
    The Nursing Minimum Data Set: Abstraction Tool for Standardized, Comparable, Essential Data Hamet H. Werley, RN, PhD, Elizabeth C. Devine, RN, PhD, Cecilia R. Zom, RN, MSN, Polly Ryan, RN, MSN, and Bonnie L. Westra, RN, MSN Inrducdion is a system that can be used by public health nurses in theirpractice and for com- With the rapid explosion of nursing parison of nursing care and resource con- knowledge worldwide, the amount ofdata sumption across other settings, thus pro- nurses use and process in the delivery of viding linkage to all other nursing care care is extensive and often unmanageable. settings. Advances in information management In addition to providing a mechanism and computer technology have broad im- for the comparison of nursing care data plications for this knowledge explosion across settings, the Nursing Minimum and can facilitate the collection, manipu- Data Set can be combined with the more lation, and retrieval of essential nursing detailed data accumulated in nursing in- data for practice and research. A uniform formation systems and other health care standardized data base that will allow for information systems. In the future, it is the grouping and comparison of nursing anticipated that these nursing information across various data collected populations, will be both and in settings, geographic locations, and time systems computerized existence at the institutional level, would be a boon to both assessing and where, comparing nursing care provided and re- through data-base management systems, sources used, as well as to research. Eli the nursing data can be linked to other Ginzberg,1 in reviewing nursing's past and health data.
    [Show full text]
  • A Proposal for an Austrian Nursing Minimum Data Set (NMDS) a Delphi Study R
    Research Article – ehealth2014 special topic 538 A Proposal for an Austrian Nursing Minimum Data Set (NMDS) A Delphi Study R. Ranegger1; W.O. Hackl2; E. Ammenwerth2 1Steiermärkische Krankenanstaltengesellschaft m.b.H., Management / Pflege, Austria; 2Institute of Health Informatics, UMIT – University for Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria Keywords Nursing minimum data set, minimal data set, nursing informatics, health statistics, Austria Summary Objective: Nursing Minimum Data Sets can be used to compare nursing care across clinical popu- lations, settings, geographical areas, and time. NMDS can support nursing research, nursing man- agement, and nursing politics. However, in contrast to other countries, Austria does not have a uni- fied NMDS. The objective of this study is to identify possible data elements for an Austrian NMDS. Methods: A two-round Delphi survey was conducted, based on a review of available NMDS, 22 ex- pert interviews, and a focus group discussion. Results: After reaching consensus, the experts proposed the following 56 data elements for an NMDS: six data elements concerning patient demographics, four data elements concerning data of the healthcare institution, four data elements concerning patient’s medical condition, 20 data el- ements concerning patient problems (nursing assessment, nursing diagnoses, risk assessment), eight data elements concerning nursing outcomes, 14 data elements concerning nursing interven- tions, and no additional data elements concerning nursing intensity. Conclusion: The proposed NMDS focuses on the long-term and acute care setting. It must now be implemented and tested in the nursing practice. Correspondence to: Appl Clin Inform 2014; 5: 538–547 Renate Ranegger http://dx.doi.org/10.4338/ACI-2014-04-RA-0027 Steiermärkische Krankenanstaltenges.m.b.H., received: April 4, 2014 Management / Pflege accepted: April 30, 2014 Stiftingtalstraße 4–6 published: June 4, 2014 8010 Graz, Austria Citation: Ranegger R, Hackl WO, Ammenwerth E.
    [Show full text]
  • July 2018 Long-Term Care Workforce Development
    Long-Term Care Workforce Development Session #2 Monday, July 30, 2018 1:00 p.m. to 5:00 p.m. Washington Department of Health, Tumwater Campus Point Plaza East Rooms 152/153, 310 Israel Road SE Tumwater, WA 98501 agenda Workgroup Tracy Rude, Representative Eileen Cody, Senator Steve Conway, Candace Goehring, Members: Rachel McAloon, Trina Crawford, Lori Banaszak, Pamela Pasquale, Abby Solomon, John Ficker, Patricia Hunter, and Alexis Wilson DOH Staff: Paula Meyer, Mindy Schaffner, Amber Zawislak, Kathy Moisio, Bobbi Allison Facilitator: Porsche Everson Guest Speakers: Kathy Moisio, NCQAC Education Consultant Lorrie Mahar, Office Chief, DSHS/ALTSA Please Read: • Long-Term Care Workgroup Plan (revised) • Packet of Relevant Information Links to the packet material can be found on the project website: https://www.doh.wa.gov/LicensesPermitsandCertificates/NursingCommission Meeting Goals CNA Standardized Curriculum: a) Identify and describe current types of CNA training programs, including apprenticeship or apprenticeship-like programs and address curriculum and program length for each type. b) Identify current minimum requirements for all CNA training programs. c) Identify current training requirements for the care of clients with dementia, developmental disabilities, and mental health issues. d) Evaluate and make recommendations for standardized CNA training curriculum a. What to keep b. What to take out c. What to update/change d. Specific training requirements for the care of clients with dementia, developmental disabilities, and mental health issues e) Identify additional work or research that may need to be done f) Brainstorm potential recommendations agenda 1:00 – 1:05 p.m. Welcome Tracy Rude, NCQAC Chair and LTCW Chair 1:05 – 1:15 p.m.
    [Show full text]