Knowledge Discovery in Databases: Improving Quality in Homecare

Size: px
Start display at page:

Download "Knowledge Discovery in Databases: Improving Quality in Homecare"

Transcription

1 Knowledge Discovery in Databases: Improving Quality in Homecare Bonnie L. Westra, PhD, RN, Assistant Professor University of Minnesota, School of Nursing An educational update to the HIMSS Management Engineering Performance Improvement Task Force June 17,

2 Acknowledgments Co-Investigators Kay Savik, MS John H. Holmes, PhD Cristina Oancea, MS, PhD Student (RA) Lynn Choromanski, MS, RN, PhD Student (RA) Mary Dierich, MS, RN, PhD Student Industrial Partners CareFacts Information Systems CHAMP Software Deb Solomon, RN, MS, Home Caring & Hospice (consultant) Funding University of Minnesota Digital Technology Initiative Grant, UMN-Grant-In-Aide, NIH Health Trajectory P20 Grant

3 Objectives Describe current homecare research using EHR data Demonstrate a series of steps in comparing traditional statistical analytic methods with knowledge discovery methods (data mining) Examine lessons learned with the use of EHR data quality improvement Explore the use of KDD for future research

4 Problem Increasing homecare/ community-based care Annual expenditure in 2005 of $47.5 billion 2000 CMS implemented PPS for Medicare patients Concern about decrease in service/ visits on outcomes First study - 28% hospitalization rate nationally remained constant Limited research on ways to reduce hospitalization

5 Research Aims The purpose of the first study was to develop predictive models for risk factors associated with increased likelihood of hospitalization of homecare patients and discover if interventions documented as part of routine care using the Omaha System influence hospitalization. Use knowledge discovery in databases combined with traditional statistics. Reported here is the first models using traditional statistics.

6 Design/ Sample Secondary analysis of EHR data OASIS and Omaha System interventions from two different EHR systems and 15 homecare agencies. Data included All patients in 2004 receiving homecare services with a minimum of two OASIS records for the start and end of an episode of care and who also had Omaha System interventions.

7 * * KDD Process * * * Fayyad UM, Piatetsky-Shapiro G, Smyth P, Uthurusamy R. Advances in knowledge discovery and data mining. Menlo Park, CA: AAI Press/ The MIT Press Press; 1996.

8 Expertise Required Clinical expert What data are collected, when, why, and how Interpretation of the data Meaningful decisions throughout the process Information system knowledge - specifying requirements What data are available Similarity across agencies and vendors Data base issues how the data are stored Data analysis Statistical knowledge Data mining knowledge Clinical validation throughout the process

9 OASIS Data

10 Omaha System ENVIRONMENTAL OMAHA SYSTEM PROBLEMS 22 - Dentition 1 - Income 23 - Cognition 2 - Sanitation 24 - Pain 3 - Residence 25 - Consciousness 4 - Neighborhood/workplace safety 26 - Integument 27 - Neuro-musculo-skeletal 5 - Other function PSYCHSOCIAL 28 - Respiration 6 - Communication with community resources 29 - Circulation 7 - Social contact 30 - Digestion-hydration 8 - Role change 31 - Bowel function 9 - Interpersonal relationship 32 - Genito-urinary function 10 - Spiritual distress 33 - Antepartum/postpartum 11 - Grief 34 - Other 12 - Emotional stability HEATH RELATED BEHAVIORS 13 - Human sexuality 35 - Nutrition 14 - Caretaking/parenting 36 - Sleep and rest patterns 15 - Neglected child/adult 37 - Physical activity 16 - Abused child/adult 38 - Personal hygiene 17 - Growth and development 39 - Substance use 18 - Other 40 - Family planning PHYSIOLOGICAL 41 - Health care supervision 19 - Hearing 42 - Prescribed medication regimen 20 - Vision 43 - Technical procedure 21 - Speech and language 44 - Other

11 Analyses Traditional statistical analyses Frequencies, descriptive, histograms Chi square/ bivariate association Latent class analysis Logistic regression analysis Future - Data mining techniques Visualization Feature selection Decision trees Clustering

12 Preprocessing 18,067 OASIS records for 3,199 patients Missing data Duplicate records Invalid values 989,772 Omaha System Interventions Missing data Matched patients with OASIS and Omaha System Data 65,000 Medication records

13 Data Preparation Preparation cleaning data Missing values Duplicate records Out of range values Grouping data into episodes of care

14 Unit of Analysis

15 2,806 patients - 4,242 Episodes Episodes Death, 1.7% Continue, 10.9% Discharge, 48.8% Transfer, 38.6%

16 Transformation Summative scales Prognosis, Pain, Pressure Ulcers, Stasis Ulcers, Surgical Wounds, Respiratory Status, ADLs, IADLs Clinical Classification Software Primary diagnoses and then reduced into 51 smaller groups within 11 major categories Charlson Index of Comorbidity Additional medical diagnoses Interventions Theoretically grouped into 23 categories Created dummy variables For non-normally distributed data

17 11 Groups Primary Diagnoses Categories 51 Clinical Classification Software Groups 260 Primary Diagnoses ICD 9 codes ~13,000

18 Clinical Classification Software Grouping CCS Categories Descriptors Cardiac and Other Circulation Diseases 24 97, 98, 99, 111, 112, 113, 117, 120, 121 Hypertension & other circulatory diseases , 101, 102 Myocardial infarction , 104, 96, 213, 245 Other heart disease , 106 Conduction Congestive Heart Failure; NONHP , 110 Acute cerebrovascular disease , 116, 118, 119 Peripheral atherosclerosis Aneurysm

19 Applying a Clusterer: Identifying similarities and dissimilarities

20 Data Analysis Latent class analysis ADL Scale (M0640 M0710) Who Provides Assistance (M0350) Management of medications (M0780) Diagnosis group (M0230 CCS Groups) Logistic regression Create models for predictors of hospitalization - OASIS Added interventions Omaha System Interventions

21 Demographics 2,806 patients Mean age 74.4 (SD = 14.1) 64.6% Females 97.9% White 4,242 Episodes Length of stay ranged from 1-6,354 days (Median = 38 days) 48.8% discharged 38.6% transfer to inpatient setting 1,620 (38.4%) hospitalized 29.9% continued with care 1.7% died

22 Demographics Primary diagnoses (most frequent) 18.8% 18.1% 9.1% 7.3% 2.3% cardiac and circulatory diseases orthopedic/ trauma surgery and follow up endocrine and nutrition respiratory problems infectious diseases Charlson Index of Comorbidity 0 10 with a mean of.58 (SD = 1.32) Interventions (384,081) 62.5% 44.9% 30.2% 16.0% monitoring teaching treatments case management

23

24 Class I: Functionally Impaired Risk Factors Risk of Hospitalization Assistance with IADLs Expected Prognosis Charlson Index Medicare as homecare payor

25 Significant Interventions Class I: Functionally Impaired Significant Interventions Variable Frequency OR Monitoring Injury Prevention Moderate 1.7

26 Risk Factors Class III: Cardiac/ Circulatory Risk of Hospitalization IADL Status: Expected Prognosis: Pain Charlson Index Bowel Incontinence 2.0 Patient equipment 3.9

27 Significant Interventions Class III: Cardiac/ Circulatory Significant Interventions Variable Frequency OR Teaching Disease Treatment Moderate.50 Providing Medication Treatment Low 1.9 Teaching Disease Treatment High 3.0

28 Interpreting Results Who Interprets Nurses on research team Homecare clinical manager Broader homecare audience What were they asked? Latent Classes are they meaningful? Within class predictors What does it mean to have bowel incontinence as a predictor of hospitalization? Across classes: most consistent predictors of hospitalization are Charlson Index of Comorbidity, Prognosis Medicare Patient management of equipment IADLs

29 Discussion Homecare patients are heterogeneous in needs latent class analysis was useful ADLs, management or oral medications, caregiver assistance, and primary diagnoses Differences between classes Similarities across classes Most consistent predictors of hospitalization are Charlson Index of Comorbidity, prognosis, Medicare, patient management of equipment, and IADLs The addition of interventions to the predictive models for hospitalization modified some predictors - Injury prevention Some interventions were risk factors, others were protective

30 Is There a Better Way? Use KDD methods How are they similar or different? What can we learn compared with traditional statistical analyses? What are the strengths and weaknesses?

31 Definition Knowledge discovery in databases (KDD) Rigorous analytic approach Combines traditional statistical concepts with semi-automated analyses Uses tools from the statistical and machine learning Inductive, data driven approach to analyze large, complex datasets Identify patterns in data that could be missed using only traditional analytic methods. Witten IH, Frank E. Data Mining: Practical Machine Learning Tools and Techniques. Second Edition ed. San Francisco: Morgan Kaufmann; 2005.

32 Traditional Statistics KDD Feature Selection Chi-Square, bivariate Chi-Square InfoGain CFS evaluation Clustering Latent Class K Means EM BestFirst Greedy Stepwise Genetic Predictive Modeling Logistic Regression Decision Trees Bayesian Network

33 Strengths & Weaknesses Traditional Statistics Well known and accepted Use to discover and test hypotheses Limited by statistical assumptions KDD Newer and treated with suspicion Used for discovery Much more flexible in working with data Requires more interaction in making decisions about data Health care data is temporal and non-retangular

34 Lessons Learned Health care data are messy audit, Audit, AUDIT!! 80% is data preparation (minimally) Know your data dwell in the data early and often Many decisions made to manage the data each could influence the validity of the results Incorrectly coded data Missing data Data reduction strategies Feature selection cut points Dummy variables cut points

35 Lessons Learned Walk before you run Phasing in steps with each subsequent study Comparisons between traditional and data mining techniques Both use similar math Difference in assumptions and how data are managed Data mining - discovery Traditional statistics discovery & verification Art and a science

36 Research in Process Predict outcomes using protective / risk factors (OASIS), interventions (Omaha System) and medication data Hospitalization and emergent care use (DTI) Pressure ulcers and incontinence (P20) Oral medication management/ ambulation (GIA) Clustering of interventions

37 Bonnie Westra, PhD, RN Assistant Professor & Co-Director ICNP Center University of Minnesota, School of Nursing Robert Wood Johnson, Nurse Executive Fellow Weaver-Densford Hall 308 Harvard St. SE Minneapolis, MN W F westr006@umn.edu

38 Thank you! For more information, please contact HIMSS Staff Liaison JoAnn W. Klinedinst, CPHIMS, PMP, FHIMSS at

Lessons Learned Reuse of EHR Data for Research and Quality Improvement

Lessons Learned Reuse of EHR Data for Research and Quality Improvement Lessons Learned Reuse of EHR Data for Research and Quality Improvement Bonnie L. Westra, PhD, RN, FAAN Assistant Professor, Co-Director ICNP Center for Nursing Minimum Data Set Knowledge Discovery University

More information

OASIS-B1 and OASIS-C Items Unchanged, Items Modified, Items Dropped, and New Items Added.

OASIS-B1 and OASIS-C Items Unchanged, Items Modified, Items Dropped, and New Items Added. Items Added. OASIS-B1 Items UNCHANGED on OASIS-C OASIS-C Item # M0014 M0016 M0020 M0030 M0032 M0040 M0050 M0060 M0063 M0064 M0065 M0066 M0069 M0080 M0090 M0100 M0110 M0220 M1005 M1030 M1200 M1230 M1324

More information

Objectives 2/23/2011. Crossing Paths Intersection of Risk Adjustment and Coding

Objectives 2/23/2011. Crossing Paths Intersection of Risk Adjustment and Coding Crossing Paths Intersection of Risk Adjustment and Coding 1 Objectives Define an outcome Define risk adjustment Describe risk adjustment measurement Discuss interactive scenarios 2 What is an Outcome?

More information

Scottish Hospital Standardised Mortality Ratio (HSMR)

Scottish Hospital Standardised Mortality Ratio (HSMR) ` 2016 Scottish Hospital Standardised Mortality Ratio (HSMR) Methodology & Specification Document Page 1 of 14 Document Control Version 0.1 Date Issued July 2016 Author(s) Quality Indicators Team Comments

More information

Predicting 30-day Readmissions is THRILing

Predicting 30-day Readmissions is THRILing 2016 CLINICAL INFORMATICS SYMPOSIUM - CONNECTING CARE THROUGH TECHNOLOGY - Predicting 30-day Readmissions is THRILing OUT OF AN OLD MODEL COMES A NEW Texas Health Resources 25 hospitals in North Texas

More information

Attachment C: Itemized List of OASIS Data Elements

Attachment C: Itemized List of OASIS Data Elements Attachment C: Itemized List of OASIS Data Item Description Number of Data SOC ROC FU TOC DTH DIS M0010 CMS Certification Number 1 1 M0014 Branch State 1 1 M0016 Branch ID Number 1 1 M0018 National Provider

More information

Executive Summary. This Project

Executive Summary. This Project Executive Summary The Health Care Financing Administration (HCFA) has had a long-term commitment to work towards implementation of a per-episode prospective payment approach for Medicare home health services,

More information

Predicting use of Nurse Care Coordination by Patients in a Health Care Home

Predicting use of Nurse Care Coordination by Patients in a Health Care Home Predicting use of Nurse Care Coordination by Patients in a Health Care Home Catherine E. Vanderboom PhD, RN Clinical Nurse Researcher Mayo Clinic Rochester, MN USA 3 rd Annual ICHNO Conference Chicago,

More information

Normalizing Flowsheet Data for Continuing Use to Meet Multiple Clinical Quality & Research Needs

Normalizing Flowsheet Data for Continuing Use to Meet Multiple Clinical Quality & Research Needs Normalizing Flowsheet Data for Continuing Use to Meet Multiple Clinical Quality & Research Needs Beverly A. Christie, DNP, RN Bonnie L. Westra, PhD, RN, FAAN, FACMI Additional Authors Steven G. Johnson,

More information

National Hospice and Palliative Care OrganizatioN. Facts AND Figures. Hospice Care in America. NHPCO Facts & Figures edition

National Hospice and Palliative Care OrganizatioN. Facts AND Figures. Hospice Care in America. NHPCO Facts & Figures edition National Hospice and Palliative Care OrganizatioN Facts AND Figures Hospice Care in America 2017 Edition NHPCO Facts & Figures - 2017 edition Table of Contents 2 Introduction 2 About this report 2 What

More information

Using Data Science to Influence Population Health

Using Data Science to Influence Population Health Using Data Science to Influence Population Health Session #NI3, February 19, 2017 Karen A. Monsen, PhD, RN, FAAN, Associate Professor University of Minnesota School of Nursing 1 Speaker Introduction Karen

More information

CASPER Reports. Objectives: What is Casper? 4/27/2012. Certification And Survey Provider Enhanced Reports

CASPER Reports. Objectives: What is Casper? 4/27/2012. Certification And Survey Provider Enhanced Reports CASPER Reports By Cindy Skogen, RN Oasis Education Coordinator at MDH Contact #: 651-201-4314 E-mail: Health.OASIS@state.mn.us Source: Center for Medicare/Medicaid Services (CMS). Objectives: Following

More information

OASIS QUALITY IMPROVEMENT REPORTS

OASIS QUALITY IMPROVEMENT REPORTS 6 OASIS QUALITY REPORTS GENERAL INFORMATION... 2 AGENCY PATIENT-RELATED CHARACTERISTICS (CASE MIX) REPORT... 4 AGENCY PATIENT-RELATED CHARACTERISTICS (CASE MIX) TALLY REPORT 9 HHA REVIEW AND CORRECT REPORT...13

More information

William B. Saunders, PhD, MPH Program Director, Health Informatics PSM & Certificate Programs. Laura J. Dunlap, RN

William B. Saunders, PhD, MPH Program Director, Health Informatics PSM & Certificate Programs. Laura J. Dunlap, RN William B. Saunders, PhD, MPH Program Director, Health Informatics PSM & Certificate Programs Laura J. Dunlap, RN Background Research Questions Methods Results for North Carolina Results for Specific Counties

More information

Leveraging Your Facility s 5 Star Analysis to Improve Quality

Leveraging Your Facility s 5 Star Analysis to Improve Quality Leveraging Your Facility s 5 Star Analysis to Improve Quality DNS/DSW Conference November, 2016 Presented by: Kathy Pellatt, Senior Quality Improvement Analyst, LeadingAge NY Susan Chenail, Senior Quality

More information

Hospice and End of Life Care and Services Critical Element Pathway

Hospice and End of Life Care and Services Critical Element Pathway Use this pathway for a resident identified as receiving end of life care (e.g., palliative care, comfort care, or terminal care) or receiving hospice care from a Medicare-certified hospice. Review the

More information

Determining Like Hospitals for Benchmarking Paper #2778

Determining Like Hospitals for Benchmarking Paper #2778 Determining Like Hospitals for Benchmarking Paper #2778 Diane Storer Brown, RN, PhD, FNAHQ, FAAN Kaiser Permanente Northern California, Oakland, CA, Nancy E. Donaldson, RN, DNSc, FAAN Department of Physiological

More information

Transitions Through the Care Continuum: Discussions on Barriers to Patient Care, Communications, and Advocacy

Transitions Through the Care Continuum: Discussions on Barriers to Patient Care, Communications, and Advocacy Transitions Through the Care Continuum: Discussions on Barriers to Patient Care, Communications, and Advocacy Scott Matthew Bolhack, MD, MBA, CMD, CWS, FACP, FAAP April 29, 2017 Disclosure Slide I have

More information

Using Structured Post Acute Assessment Data as the Raw Material for Predictive Modeling. Speaker: Thomas Martin November 2014

Using Structured Post Acute Assessment Data as the Raw Material for Predictive Modeling. Speaker: Thomas Martin November 2014 Using Structured Post Acute Assessment Data as the Raw Material for Predictive Modeling Speaker: Thomas Martin November 2014 1 Learning Objectives SNF s place in continuum of care Large variance across

More information

Objectives 9/18/2018. Patient Driven Payment Model(PDPM) Janine Finck Boyle, MBA/HCA, LNHA Vice President of Regulatory Affairs Fall 2018

Objectives 9/18/2018. Patient Driven Payment Model(PDPM) Janine Finck Boyle, MBA/HCA, LNHA Vice President of Regulatory Affairs Fall 2018 Patient Driven Payment Model(PDPM) Janine Finck Boyle, MBA/HCA, LNHA Vice President of Regulatory Affairs Fall 2018 Mission: The trusted voice for aging. Objectives List the five(5) case mix components

More information

CASE-MIX ANALYSIS ACROSS PATIENT POPULATIONS AND BOUNDARIES: A REFINED CLASSIFICATION SYSTEM DESIGNED SPECIFICALLY FOR INTERNATIONAL USE

CASE-MIX ANALYSIS ACROSS PATIENT POPULATIONS AND BOUNDARIES: A REFINED CLASSIFICATION SYSTEM DESIGNED SPECIFICALLY FOR INTERNATIONAL USE CASE-MIX ANALYSIS ACROSS PATIENT POPULATIONS AND BOUNDARIES: A REFINED CLASSIFICATION SYSTEM DESIGNED SPECIFICALLY FOR INTERNATIONAL USE A WHITE PAPER BY: MARC BERLINGUET, MD, MPH JAMES VERTREES, PHD RICHARD

More information

MEASURING POST ACUTE CARE OUTCOMES IN SNFS. David Gifford MD MPH American Health Care Association Atlantic City, NJ Mar 17 th, 2015

MEASURING POST ACUTE CARE OUTCOMES IN SNFS. David Gifford MD MPH American Health Care Association Atlantic City, NJ Mar 17 th, 2015 MEASURING POST ACUTE CARE OUTCOMES IN SNFS David Gifford MD MPH American Health Care Association Atlantic City, NJ Mar 17 th, 2015 Principles Guiding Measure Selection PAC quality measures need to Reflect

More information

Exhibit A. Part 1 Statement of Work

Exhibit A. Part 1 Statement of Work Exhibit A Part 1 Statement of Work Contractor shall provide Basic Neurological services as described herein to Medicaid eligible Clients who are authorized to receive services at the Contractor s owned

More information

Health Economics Program

Health Economics Program Health Economics Program Issue Brief 2006-02 February 2006 Health Conditions Associated With Minnesotans Hospital Use Health care spending by Minnesota residents accounts for approximately 12% of the state

More information

Home Health Care Outcomes Under Capitated and Fee-for-Service Payment

Home Health Care Outcomes Under Capitated and Fee-for-Service Payment Home Health Care Outcomes Under Capitated and Fee-for-Service Payment Peter W. Shaughnessy, Ph.D., Robert E. Schlenker, Ph.D., and David F. Hittle, Ph.D. In this article, case-mix-adjusted outcomes of

More information

Key points. Home Care agency structures. Introduction to Physical Therapy in the Home Care Setting. Home care industry

Key points. Home Care agency structures. Introduction to Physical Therapy in the Home Care Setting. Home care industry Introduction to Physical Therapy in the Home Care Setting Home Health Section of APTA Key points Home care industry Client populations Prospective Payment System (PPS) Physical therapy services Assessment

More information

Long-Stay Alternate Level of Care in Ontario Mental Health Beds

Long-Stay Alternate Level of Care in Ontario Mental Health Beds Health System Reconfiguration Long-Stay Alternate Level of Care in Ontario Mental Health Beds PREPARED BY: Jerrica Little, BA John P. Hirdes, PhD FCAHS School of Public Health and Health Systems University

More information

Specialized On-Demand Education for Home Care Staff

Specialized On-Demand Education for Home Care Staff Home Care Association of New Hampshire and RCTCLearn offer Specialized On-Demand Education for Home Care Staff Providing your agency s staff with high quality continuing professional education doesn t

More information

Attachment A - Comparison of OASIS-C (Current Version) to OASIS-C1 (Proposed Data Collection)

Attachment A - Comparison of OASIS-C (Current Version) to OASIS-C1 (Proposed Data Collection) Attachment A - Comparison of OASIS-C (Current Version) to (Proposed Data Collection) OASIS-C M0010 CMS Certification Number S M0010 CMS Certification Number M0014 Branch State S M0014 Branch State S M0016

More information

Work In Progress August 24, 2015

Work In Progress August 24, 2015 Presenter Sarah Wilson MSOTR/L, CHT, CLT 4 th year PhD student at NOVA Southeastern University Practicing OT for 14 years Have worked for Washington Orthopedics and Sports Medicine for the last 8 years

More information

An Overview of Ohio s In-Home Service Program For Older People (PASSPORT)

An Overview of Ohio s In-Home Service Program For Older People (PASSPORT) An Overview of Ohio s In-Home Service Program For Older People (PASSPORT) Shahla Mehdizadeh Robert Applebaum Scripps Gerontology Center Miami University May 2005 This report was produced by Lisa Grant

More information

STATISTICAL BRIEF #9. Hospitalizations among Males, Highlights. Introduction. Findings. June 2006

STATISTICAL BRIEF #9. Hospitalizations among Males, Highlights. Introduction. Findings. June 2006 HEALTHCARE COST AND UTILIZATION PROJECT STATISTICAL BRIEF #9 Agency for Healthcare Research and Quality June 2006 Hospitalizations among Males, 2003 C. Allison Russo, M.P.H. and Anne Elixhauser, Ph.D.

More information

Reducing Readmissions: Potential Measurements

Reducing Readmissions: Potential Measurements Reducing Readmissions: Potential Measurements Avoid Readmissions Through Collaboration October 27, 2010 Denise Remus, PhD, RN Chief Quality Officer BayCare Health System Overview Why Focus on Readmissions?

More information

Preventing Heart Failure Readmissions by Using a Risk Stratification Tool

Preventing Heart Failure Readmissions by Using a Risk Stratification Tool Preventing Heart Failure Readmissions by Using a Risk Stratification Tool Anna Dermenchyan, MSN, RN, CCRN-K Senior Clinical Quality Specialist Department of Medicine, UCLA Health PhD Student, UCLA School

More information

Best Options for Responding to the Home Health PPS 2011 Cuts *revised handouts

Best Options for Responding to the Home Health PPS 2011 Cuts *revised handouts Best Options for Responding to the Home Health PPS 2011 Cuts *revised handouts Improve Your Revenues with OASIS and Coding Presented By: Rhonda Marie Will, RN, BS, HCS-D, COS-C Melanie R. Duerr, RN, MS,

More information

MDS 3.0/RUG IV OVERVIEW

MDS 3.0/RUG IV OVERVIEW MDS 3.0/RUG IV Distance Learning Series January - May 2016 OVERVIEW In keeping with the success of their previous highly-rated distance learning education offerings, LeadingAge state affiliates and Plante

More information

OASIS-C Home Health Outcome Measures

OASIS-C Home Health Outcome Measures OASIS-C Home Measures 1 End Result Grooming groom self. (M1800) Grooming 2 End Result Grooming same in ability to groom self. (M1800) Grooming 3 End Result Upper Body Dressing dress upper body. (M1810)

More information

Chapter 11. Expanding Roles and Functions of the Health Information Management and Health Informatics Professional

Chapter 11. Expanding Roles and Functions of the Health Information Management and Health Informatics Professional Chapter 11 Expanding Roles and Functions of the Health Information Management and Health Informatics Professional 11-2 Learning Outcomes When you finish this chapter, you will be able to: 11.1 Discuss

More information

Using Clinical Criteria for Evaluating Short Stays and Beyond. Georgeann Edford, RN, MBA, CCS-P. The Clinical Face of Medical Necessity

Using Clinical Criteria for Evaluating Short Stays and Beyond. Georgeann Edford, RN, MBA, CCS-P. The Clinical Face of Medical Necessity Using Clinical Criteria for Evaluating Short Stays and Beyond Georgeann Edford, RN, MBA, CCS-P The Clinical Face of Medical Necessity 1 The Documentation Faces of Medical Necessity ç3 Setting the Stage

More information

CURRICULUM VITAE TRACY K. FASOLINO

CURRICULUM VITAE TRACY K. FASOLINO ADDRESS: CURRICULUM VITAE TRACY K. FASOLINO Office: School of Nursing, 403 Edwards Hall, Clemson University, Clemson, South Carolina 29634 PHONE: 864-656-5087 (w) E-MAIL: tfasoli@clemson.edu EDUCATION:

More information

NURSING. Class Lab Clinical Credit NUR 111 Intro to Health Concepts Prerequisites: None Corequisites: None

NURSING. Class Lab Clinical Credit NUR 111 Intro to Health Concepts Prerequisites: None Corequisites: None NURSING Class Lab Clinical Credit NUR 111 Intro to Health Concepts 4 6 6 8 Prerequisites: None Corequisites: None Course Description This course introduces the concepts within the three domains of the

More information

TITLE/DESCRIPTION: Admission and Discharge Criteria for Telemetry

TITLE/DESCRIPTION: Admission and Discharge Criteria for Telemetry TITLE/DESCRIPTION: Admission and Discharge Criteria for Telemetry DEPARTMENT: PERSONNEL: Telemetry Telemetry Personnel EFFECTIVE DATE: 6/86 REVISED: 02/00, 4/10, 12/14 Admission Procedure: 1. The admitting

More information

AN OPPORTUNITY TO INTEGRATE NUTRITION SERVICES IN YOUR LOCAL HEALTHCARE SYSTEM

AN OPPORTUNITY TO INTEGRATE NUTRITION SERVICES IN YOUR LOCAL HEALTHCARE SYSTEM AN OPPORTUNITY TO INTEGRATE NUTRITION SERVICES IN YOUR LOCAL HEALTHCARE SYSTEM KIMBERLY K. DELP, RN BSN January 26, 2017 AN OPPORTUNITY TO INTEGRATE NUTRITION SERVICES IN YOUR LOCAL HEALTHCARE SYSTEM 1

More information

How BC s Health System Matrix Project Met the Challenges of Health Data

How BC s Health System Matrix Project Met the Challenges of Health Data Big Data: Privacy, Governance and Data Linkage in Health Information How BC s Health System Matrix Project Met the Challenges of Health Data Martha Burd, Health System Planning and Innovation Division

More information

Institute on Medicare and Medicaid Payment Issues March 28 30, 2012 Robert A. Pelaia, JD, CPC

Institute on Medicare and Medicaid Payment Issues March 28 30, 2012 Robert A. Pelaia, JD, CPC I. Introduction Institute on Medicare and Medicaid Payment Issues March 28 30, 2012 Robert A. Pelaia, JD, CPC Senior University Counsel for Health Affairs - Jacksonville 904-244-3146 robert.pelaia@jax.ufl.edu

More information

Basic Training: Home Health Edition. OASIS and Outcomes. April 2, 2013

Basic Training: Home Health Edition. OASIS and Outcomes. April 2, 2013 Basic Training: Home Health Edition OASIS and Outcomes April 2, 2013 Presented by: Rhonda Will, RN, BS, COS-C, BCHH-C, Assistant Director of the Competency Institute, Fazzi Associates, Inc. 243 King Street,

More information

Documentation. The learner will be able to :

Documentation. The learner will be able to : Functional Decline in Hospice Assessment, Intervention, & Objectives The learner will be able to : Assess functional decline utilizing appropriate evidence based tools Document functional indicators and

More information

Case-mix Analysis Across Patient Populations and Boundaries: A Refined Classification System

Case-mix Analysis Across Patient Populations and Boundaries: A Refined Classification System Case-mix Analysis Across Patient Populations and Boundaries: A Refined Classification System Designed Specifically for International Quality and Performance Use A white paper by: Marc Berlinguet, MD, MPH

More information

Understanding Patient Choice Insights Patient Choice Insights Network

Understanding Patient Choice Insights Patient Choice Insights Network Quality health plans & benefits Healthier living Financial well-being Intelligent solutions Understanding Patient Choice Insights Patient Choice Insights Network SM www.aetna.com Helping consumers gain

More information

Comparison of Care in Hospital Outpatient Departments and Physician Offices

Comparison of Care in Hospital Outpatient Departments and Physician Offices Comparison of Care in Hospital Outpatient Departments and Physician Offices Final Report Prepared for: American Hospital Association February 2015 Berna Demiralp, PhD Delia Belausteguigoitia Qian Zhang,

More information

Standardized Terminologies, Information Technology, Objectives. Trendssssss!

Standardized Terminologies, Information Technology, Objectives. Trendssssss! Standardized Terminologies, Information Technology, and the Real World Karen S. Martin, RN, MSN, FAAN Sue Moorhead, RN, PhD Kathy Lesh, RN BC, EdM, MS Wheel of Fortune Objectives Summarize ANA recognized

More information

Is there an impact of Health Information Technology on Delivery and Quality of Patient Care?

Is there an impact of Health Information Technology on Delivery and Quality of Patient Care? Is there an impact of Health Information Technology on Delivery and Quality of Patient Care? Amanda Hessels, PhD, MPH, RN, CIC, CPHQ Nurse Scientist Meridian Health, Ann May Center for Nursing 11.13.2014

More information

Comparative Effectiveness Research and Patient Centered Outcomes Research in Public Health Settings: Design, Analysis, and Funding Considerations

Comparative Effectiveness Research and Patient Centered Outcomes Research in Public Health Settings: Design, Analysis, and Funding Considerations University of Kentucky UKnowledge Health Management and Policy Presentations Health Management and Policy 12-7-2012 Comparative Effectiveness Research and Patient Centered Outcomes Research in Public Health

More information

Development of Updated Models of Non-Therapy Ancillary Costs

Development of Updated Models of Non-Therapy Ancillary Costs Development of Updated Models of Non-Therapy Ancillary Costs Doug Wissoker A. Bowen Garrett A memo by staff from the Urban Institute for the Medicare Payment Advisory Commission Urban Institute MedPAC

More information

Nursing Fundamentals

Nursing Fundamentals Western Technical College 10543101 Nursing Fundamentals Course Outcome Summary Course Information Description Career Cluster Instructional Level Total Credits 2.00 This course focuses on basic nursing

More information

Factors influencing patients length of stay

Factors influencing patients length of stay Factors influencing patients length of stay Factors influencing patients length of stay YINGXIN LIU, MIKE PHILLIPS, AND JIM CODDE Yingxin Liu is a research consultant and Mike Phillips is a senior lecturer

More information

Quality of Care of Medicare- Medicaid Dual Eligibles with Diabetes. James X. Zhang, PhD, MS The University of Chicago

Quality of Care of Medicare- Medicaid Dual Eligibles with Diabetes. James X. Zhang, PhD, MS The University of Chicago Quality of Care of Medicare- Medicaid Dual Eligibles with Diabetes James X. Zhang, PhD, MS The University of Chicago April 23, 2013 Outline Background Medicare Dual eligibles Diabetes mellitus Quality

More information

An Initial Review of the CY Medicare Home Health Rule. CY2018 Proposed Medicare Home Health Rate Rule and Much More

An Initial Review of the CY Medicare Home Health Rule. CY2018 Proposed Medicare Home Health Rate Rule and Much More An Initial Review of the CY 2018 2019 Medicare Home Health Rule Mary K. Carr William A. Dombi NAHC CY2018 Proposed Medicare Home Health Rate Rule and Much More Published July 25, 2017 https://www.cms.gov/medicare/medicare

More information

Performance Measurement of a Pharmacist-Directed Anticoagulation Management Service

Performance Measurement of a Pharmacist-Directed Anticoagulation Management Service Hospital Pharmacy Volume 36, Number 11, pp 1164 1169 2001 Facts and Comparisons PEER-REVIEWED ARTICLE Performance Measurement of a Pharmacist-Directed Anticoagulation Management Service Jon C. Schommer,

More information

The Role of Analytics in the Development of a Successful Readmissions Program

The Role of Analytics in the Development of a Successful Readmissions Program The Role of Analytics in the Development of a Successful Readmissions Program Pierre Yong, MD, MPH Director, Quality Measurement & Value-Based Incentives Group Centers for Medicare & Medicaid Services

More information

Online Education for Home Care and Hospice from Educators You Trust. Page 1 of 7. General Education Catalog of Courses

Online Education for Home Care and Hospice from Educators You Trust. Page 1 of 7. General Education Catalog of Courses Online Education for Home Care and Hospice from Educators You Trust Page 1 of 7 General Education Catalog of Courses Contents WELCOME!... 3 APPROVALS/ACCREDITATION, TESTIMONIALS AND AFFILIATIONS... 3 HIGHER

More information

Medications: Defining the Role and Responsibility of Physical Therapy Practice

Medications: Defining the Role and Responsibility of Physical Therapy Practice This article is based on a presentation by Matt Janes, PT, DPT, MHS, OCS, CSCS, Division AVP, Therapy Practice and Quality, Kindred at Home, and Diana Kornetti, PT, MA, HCS-D, President, Home Health Section

More information

Accountable Care and Shared Savings Program Where Do Urologists Fit In?

Accountable Care and Shared Savings Program Where Do Urologists Fit In? 5 th Annual AACU State Society Network Meeting September 22-23, 2012 Accountable Care and Shared Savings Program Michael R. Callahan Katten Muchin Rosenman LLP 525 West Monroe Street Chicago, Illinois

More information

The non-executive director s guide to NHS data Part one: Hospital activity, data sets and performance

The non-executive director s guide to NHS data Part one: Hospital activity, data sets and performance Briefing October 2017 The non-executive director s guide to NHS data Part one: Hospital activity, data sets and performance Key points As a non-executive director, it is important to understand how data

More information

OASIS Complete Webinar Series

OASIS Complete Webinar Series OASIS Complete Webinar Series Selecting Clinically Relevant and Fiscally Appropriate Diagnoses Presented By: Rhonda Marie Will, RN, BS, HCS-D, COS-C October 1, 2010 243 King Street, Suite 246 Northampton,

More information

Maximizing the Power of Your Data. Peggy Connorton, MS, LNFA AHCA Director, Quality and LTC Trend Tracker

Maximizing the Power of Your Data. Peggy Connorton, MS, LNFA AHCA Director, Quality and LTC Trend Tracker Maximizing the Power of Your Data Peggy Connorton, MS, LNFA AHCA Director, Quality and LTC Trend Tracker Objectives Explore selected LTC Trend Tracker reports & features including: re-hospitalization,

More information

Enhancing Patient Care through Effective and Efficient Nursing Documentation

Enhancing Patient Care through Effective and Efficient Nursing Documentation Enhancing Patient Care through Effective and Efficient Nursing Documentation Session NI1, March 5, 2018 Jane Englebright, PhD, RN, CENP, FAAN HCA Senior Vice President & Chief Nurse Executive 1 Conflict

More information

Using the Trauma Quality Improvement Program (TQIP) Metrics Data to Change Clinical Practice Abigail R. Blackmore, MSN, RN Pamela W.

Using the Trauma Quality Improvement Program (TQIP) Metrics Data to Change Clinical Practice Abigail R. Blackmore, MSN, RN Pamela W. Using the Trauma Quality Improvement Program (TQIP) Metrics Data to Change Clinical Practice Abigail R. Blackmore, MSN, RN Pamela W. Bourg, PhD, RN, TCRN, FAEN Learning Objectives Explain the importance

More information

The Drive Towards Value Based Care

The Drive Towards Value Based Care The Drive Towards Value Based Care Thursday, March 3, 2016 Michael Aratow, MD, FACEP Chief Medical Information Officer, San Mateo Medical Center Gaurav Nagrath, MBA, Sr. Strategist, Population Health Research

More information

PSYCHIATRY SERVICES: MD FOCUSED

PSYCHIATRY SERVICES: MD FOCUSED PSYCHIATRY SERVICES: MD FOCUSED CY2013 Risk Based Scheduled Review Agenda 2 Overview of New Risk Based Scheduled Reviews Initial review findings PhD summary MD summary Examples Template/Psychotherapy Time

More information

Community Discharge and Rehospitalization Outcome Measures (Fiscal Year 2011)

Community Discharge and Rehospitalization Outcome Measures (Fiscal Year 2011) Andrew Kramer, MD Ron Fish, MBA Sung-joon Min, PhD Providigm, LLC Community Discharge and Rehospitalization Outcome Measures (Fiscal Year 2011) A report by staff from Providigm, LLC, for the Medicare Payment

More information

Maternal and Child Health North Carolina Division of Public Health, Women's and Children's Health Section

Maternal and Child Health North Carolina Division of Public Health, Women's and Children's Health Section Maternal and Child Health North Carolina Division of Public Health, Women's and Children's Health Section Raleigh, North Carolina Assignment Description The WCHS is one of seven sections/centers that compose

More information

Medicare Part A SNF Payment System Reform: Introduction to Resident Classification System - I ZIMMET HEALTHCARE 2018

Medicare Part A SNF Payment System Reform: Introduction to Resident Classification System - I ZIMMET HEALTHCARE 2018 Medicare Part A SNF Payment System Reform: Introduction to Resident Classification System - I Introduction to the Resident Classification System - I Concepts Structure Implications RCS is NOT the Unified

More information

Medical Respite Program Expansion

Medical Respite Program Expansion Medical Respite Program Expansion Alice Moughamian, RN, CNS, Program Director, Medical Respite and Sobering Center Hali Hammer, MD, Director of Primary Care SFDPH Medical Respite Program Program of SF

More information

HIMSS 2011 Implementation of Standardized Terminologies Survey Results

HIMSS 2011 Implementation of Standardized Terminologies Survey Results HIMSS 2011 Implementation of Standardized Terminologies Survey Results The current healthcare climate, with rising costs and decreased reimbursement, necessitates fiscal responsibility. Elements of the

More information

Outcomes Measurement in Long-Term Care (LTC)

Outcomes Measurement in Long-Term Care (LTC) ASHA Short Course Outcomes Measurement in Long-Term Care (LTC) Bill Goulding, MS/CCC-SLP November 19, 2012 How Do We Show Value? Easy to measure! Not so easy! V $$$ A L Impact? Cost U Benefit E What do

More information

Cloud Analytics As A Service

Cloud Analytics As A Service Cloud Analytics As A Service Enabling Actionable Realtime Data Analytics July 13, 2016 Joanne White, CIO Mark Gerschutz, Director of IT Rick Crawford, Interface Architect Christine Wulff, RN, ED Analyst

More information

MDS 3.0: What Leadership Needs to Know

MDS 3.0: What Leadership Needs to Know MDS 3.0: What Leadership Needs to Know especially prepared for CANPFA Ann Spenard RN, MSN History of the MDS and RAI Process The Resident Assessment Instrument (RAI) was part of a set of reforms enacted

More information

Deborah Perian, RN MHA CPHQ. Reduce Unplanned Hospital Admissions: Focus on Patient Safety

Deborah Perian, RN MHA CPHQ. Reduce Unplanned Hospital Admissions: Focus on Patient Safety Deborah Perian, RN MHA CPHQ Reduce Unplanned Hospital Admissions: Focus on Patient Safety Objectives At the end of this lesson, the learner will be able to: Identify key clinical and policy issues associated

More information

Home Health Eligibility Requirements

Home Health Eligibility Requirements Presented By: Melinda A. Gaboury, COS-C Chief Executive Officer Healthcare Provider Solutions, Inc. healthcareprovidersolutions.com Home Health Eligibility Requirements Meets eligibility for home health

More information

(M1025) Case-Mix Diagnosis (Optional) OPTIONAL Complete only if a Z-code in Column 2 is reported in place of a resolved condition

(M1025) Case-Mix Diagnosis (Optional) OPTIONAL Complete only if a Z-code in Column 2 is reported in place of a resolved condition HOME HEALTH 2017 PPS CALCULATION WORKSHEET PATIENT NAME: ID NUMBER: DATE: TYPE OF ASSESSMENT: Start of care Follow-up M0110 - EPISODE TIMING: Is the Medicare home health payment episode f which this assessment

More information

Factors that Impact Readmission for Medicare and Medicaid HMO Inpatients

Factors that Impact Readmission for Medicare and Medicaid HMO Inpatients The College at Brockport: State University of New York Digital Commons @Brockport Senior Honors Theses Master's Theses and Honors Projects 5-2014 Factors that Impact Readmission for Medicare and Medicaid

More information

The Camden Coalition of Healthcare. Management

The Camden Coalition of Healthcare. Management Camden Coalition of Healthcare Providers Camden Coalition of Healthcare Providers The Camden Coalition of Healthcare Providers Approach to Risk Stratified Care Management Presentation by: Kennen S. Gross,

More information

Today s educational presentation is provided by. The software that powers HOME HEALTH. THERAPY. PRIVATE DUTY. HOSPICE

Today s educational presentation is provided by. The software that powers HOME HEALTH. THERAPY. PRIVATE DUTY. HOSPICE Today s educational presentation is provided by The software that powers HOME HEALTH. THERAPY. PRIVATE DUTY. HOSPICE At Kinnser, we believe post-acute care businesses need the right software solution for

More information

Plant the Seeds of Compliance with PEPPER. Prepared for: WiAHC June 8, Presented by: Caryn Adams, Manager

Plant the Seeds of Compliance with PEPPER. Prepared for: WiAHC June 8, Presented by: Caryn Adams, Manager Plant the Seeds of Compliance with PEPPER Prepared for: June 8, 2017 Presented by: Caryn Adams, Manager Summary and Objectives Program for Evaluating Payment Electronic Report has been available to home

More information

UNIT DESCRIPTIONS. 2 North Musculoskeletal Rehabilitative Care

UNIT DESCRIPTIONS. 2 North Musculoskeletal Rehabilitative Care UNIT DESCRIPTIONS 2 North Musculoskeletal Rehabilitative Care Musculoskeletal Rehabilitation The Musculoskeletal Service provides rehabilitation following multiple trauma, or orthopaedic surgery (primarily

More information

2015 Hospital Inpatient Discharge Data Annual Report

2015 Hospital Inpatient Discharge Data Annual Report 2015 Hospital Inpatient Discharge Data Annual Report Health Systems Epidemiology Program Epidemiology and Response Division New Mexico Department of Health 2015 Hospital Inpatient Discharge Data Report

More information

ICD-10 for Beginners Four-Part Series JLU Health Records Systems 1. ICD-10-CM Coding. & Its Impact on Reimbursement

ICD-10 for Beginners Four-Part Series JLU Health Records Systems  1. ICD-10-CM Coding. & Its Impact on Reimbursement ICD-10 for Beginners Four-Part Series www. 1 ICD-10-CM Coding & Its Impact on Reimbursement PRESENTER: Joan L. Usher, BS, RHIA, ACE AHIMA Approved ICD-10-CM Trainer JLU HEALTH RECORD SYSTEMS TEL: (781)

More information

NANDA-APPROVED NURSING DIAGNOSES Grand Total: 244 Diagnoses August 2017

NANDA-APPROVED NURSING DIAGNOSES Grand Total: 244 Diagnoses August 2017 NANDA-APPROVED NURSING DIAGNOSES 2018-2020 Grand Total: 244 Diagnoses August 2017 Indicates new diagnosis for 2018-2020--17 total Indicates revised diagnosis for 2018-2020--72 total (Retired Diagnoses

More information

National Stroke Nursing Forum Nurse Staffing of Stroke Early Supported Discharge Teams A Position Statement for Guidance of Service Developments

National Stroke Nursing Forum Nurse Staffing of Stroke Early Supported Discharge Teams A Position Statement for Guidance of Service Developments National Stroke Nursing Forum Nurse Staffing of Stroke Early Supported Discharge Teams A Position Statement for Guidance of Service Developments Introduction This paper is a position statement from the

More information

2016 Complex Case Management. Program Evaluation. Our mission is to improve the health and quality of life of our members

2016 Complex Case Management. Program Evaluation. Our mission is to improve the health and quality of life of our members 2016 Complex Case Management Program Evaluation Our mission is to improve the health and quality of life of our members 2016 Complex Case Management Program Evaluation Table of Contents Program Purpose

More information

Test Procedure for (c) Maintain up-to-date problem list

Test Procedure for (c) Maintain up-to-date problem list Test Procedure for 170.302 (c) Maintain up-to-date problem list This document describes the draft test procedure for evaluating conformance of complete EHRs or EHR modules 1 to the certification criteria

More information

New Quality Measures Will Soon Impact Nursing Home Compare and the 5-Star Rating System: What providers need to know

New Quality Measures Will Soon Impact Nursing Home Compare and the 5-Star Rating System: What providers need to know New Quality Measures Will Soon Impact Nursing Home Compare and the 5-Star Rating System: What providers need to know Presented by: Kathy Pellatt, Senior Quality Improvement Analyst LeadingAge New York

More information

Pricing and funding for safety and quality: the Australian approach

Pricing and funding for safety and quality: the Australian approach Pricing and funding for safety and quality: the Australian approach Sarah Neville, Ph.D. Executive Director, Data Analytics Sean Heng Senior Technical Advisor, AR-DRG Development Independent Hospital Pricing

More information

Tracking Functional Outcomes throughout the Continuum of Acute and Postacute Rehabilitative Care

Tracking Functional Outcomes throughout the Continuum of Acute and Postacute Rehabilitative Care Tracking Functional Outcomes throughout the Continuum of Acute and Postacute Rehabilitative Care Robert D. Rondinelli, MD, PhD Medical Director Rehabilitation Services Unity Point Health, Des Moines Paulette

More information

The curriculum is based on achievement of the clinical competencies outlined below:

The curriculum is based on achievement of the clinical competencies outlined below: ANESTHESIOLOGY CRITICAL CARE MEDICINE FELLOWSHIP Program Goals and Objectives The curriculum is based on achievement of the clinical competencies outlined below: Patient Care Fellows will provide clinical

More information

What s Happening in the Nursing Home? Cherry Meier, RN, MSN, NHA Vice President of Public Affairs

What s Happening in the Nursing Home? Cherry Meier, RN, MSN, NHA Vice President of Public Affairs What s Happening in the Nursing Home? Cherry Meier, RN, MSN, NHA Vice President of Public Affairs Objectives Describe the benefits of partnering with hospice Explain the regulations for the interface between

More information

HHGM is Alive and Kicking: How Can You Prepare for What s Next?

HHGM is Alive and Kicking: How Can You Prepare for What s Next? HHGM is Alive and Kicking: How Can You Prepare for What s Next? New England Home Care & Hospice Conference and Trade Show April 26, 2018 Presented by: Chris Attaya VP of Product Strategy, SHP Sue Payne

More information

RE-ADMITTING IN HOSPITALS: MODELS AND CHALLENGES. Murali Parthasarathy Dr. Paul Damien

RE-ADMITTING IN HOSPITALS: MODELS AND CHALLENGES. Murali Parthasarathy Dr. Paul Damien RE-ADMITTING IN HOSPITALS: MODELS AND CHALLENGES Murali Parthasarathy Dr. Paul Damien April 11, 2014 1 Major pain points Hospitals scored on five major pain points 1. Death rates among heart and surgery

More information

3M Health Information Systems. 3M Clinical Risk Groups: Measuring risk, managing care

3M Health Information Systems. 3M Clinical Risk Groups: Measuring risk, managing care 3M Health Information Systems 3M Clinical Risk Groups: Measuring risk, managing care 3M Clinical Risk Groups: Measuring risk, managing care Overview The 3M Clinical Risk Groups (CRGs) are a population

More information