Overview of Hospital Information Systems

Transcription

1 Overview of Hospital Information Systems PHARMACY INFORMATICS EDUCATIONAL SERIES โครงการอบรมการพ ฒนาและจ ดการระบบข อม ลเภส ชกรรมในโรงพยาบาล : การเตร ยมข อม ลยาเพ อการเบ กจ าย ว นท 18 ม ถ นายน 2557 คณะเภส ชศาสตร จ ฬาลงกรณ มหาว ทยาล ย บ ญช ย ก จสนาโยธ น M.D., Ph.D.(Health Informatics) นวนรรน ธ ระอ มพรพ นธ M.D., Ph.D.(Health Informatics)

2 Outline Healthcare & Information Why We Need ICT in Healthcare Health IT Hospital Information Systems Health Information Exchange Q&A 2

3 What Clinicians Want? To treat & to care for their patients to their best abilities, given limited time & resources Image Source: (Nevit Dilmen) 3

4 High Quality Care Safe Timely Effective Patient-Centered Efficient Equitable Institute of Medicine, Committee on Quality of Health Care in America. Crossing the quality chasm: a new health system for the 21st century. Washington, DC: National Academy Press; p. 4

5 Information is Everywhere in Healthcare Shortliffe EH. Biomedical informatics in the education of physicians. JAMA Sep 15;304(11):

6 Why We Need ICT in Healthcare? #1: Because information is everywhere in healthcare 6

7 Landmark IOM Reports (IOM, 2000) (IOM, 2001) (IOM, 2003) (IOM, 2011) 7

8 Patient Safety To Err is Human (IOM, 2000) reported that: 44,000 to 98,000 people die in U.S. hospitals each year as a result of preventable medical mistakes Mistakes cost U.S. hospitals $17 billion to $29 billion yearly Individual errors are not the main problem Faulty systems, processes, and other conditions lead to preventable errors Health IT Workforce Curriculum Version 3.0/Spring 2012 Introduction to Healthcare and Public Health in the US: Regulating Healthcare - Lecture d 8

9 IOM Reports Summary Humans are not perfect and are bound to make errors Highlight problems in U.S. health care system that systematically contributes to medical errors and poor quality Recommends reform Health IT plays a role in improving patient safety 9

10 To Err is Human 1: Attention Image Source: (Left) (Right) 10

11 To Err is Human 2: Memory Image Source: Suthan Srisangkaew, Department of Pathology, Facutly of Medicine Ramathibodi Hospital, Mahidol University 11

12 To Err is Human 3: Cognition Cognitive Errors - Example: Decoy Pricing The Economist Purchase Options # of People Economist.com subscription $59 Print subscription $125 Print & web subscription $ The Economist Purchase Options Economist.com subscription $59 Print & web subscription $125 # of People Ariely (2008) 12

13 Cognitive Biases in Healthcare Everyone makes mistakes. But our reliance on cognitive processes prone to bias makes treatment errors more likely than we think Klein JG. Five pitfalls in decisions about diagnosis and prescribing. BMJ Apr 2;330(7494):

14 Common Errors Medication Errors Drug Allergies Drug Interactions Ineffective or inappropriate treatment Redundant orders Failure to follow clinical practice guidelines 14

15 Why We Need ICT in Healthcare? #2: Because healthcare is error-prone and technology can help 15

16 Why We Need ICT in Healthcare? #3: Because access to high-quality patient information improves care 16

17 Health IT Use of information and communications technology (ICT) in health & healthcare settings Source: The Health Resources and Services Administration, Department of Health and Human Service, USA Slide adapted from: Boonchai Kijsanayotin 17

18 Health IT: What s in a Word? Health Information Technology Goal Value-Add Tools 18

19 Health in Health IT Patient s Health Population s Health Organization s Health (Quality, Reputation & Finance) 19

20 Various Forms of Health IT Hospital Information System (HIS) Computerized Provider Order Entry (CPOE) Electronic Health Records (EHRs) Screenshot Images from Faculty of Medicine Ramathibodi Hospital, Mahidol University Picture Archiving and Communication System (PACS) 20

21 Still Many Other Forms of Health IT Biosurveillance mhealth Personal Health Records (PHRs) and Patient Portals Telemedicine & Telehealth Images from Apple Inc., Geekzone.co.nz, Google, HealthVault.com and American Telecare, Inc. 21

22 Values of Health IT Guideline adherence Better documentation Practitioner decision making or process of care Medication safety Patient surveillance & monitoring Patient education/reminder 22

23 Enterprise-wide Hospital IT Master Patient Index (MPI) Admit-Discharge-Transfer (ADT) Electronic Health Records (EHRs) Computerized Physician Order Entry (CPOE) Clinical Decision Support Systems (CDS) Picture Archiving and Communication System (PACS) Nursing applications Enterprise Resource Planning (ERP) - Finance, Materials Management, Human Resources 23

24 Departmental IT in Hospitals Pharmacy applications Laboratory Information System (LIS) Radiology Information System (RIS) Specialized applications (ER, OR, LR, Anesthesia, Critical Care, Dietary Services, Blood Bank) Incident management & reporting system 24

25 HIS - EHR EMR PHR relationship Hospital Information Systems EHR EMR PHR EHR= Electronic Health Record EMR= Electronic Medical Record PHR= Personal Health Record

26 Computerized Provider Order Entry (CPOE) 26

27 Computerized Provider Order Entry (CPOE) Values No handwriting!!! Structured data entry: Completeness, clarity, fewer mistakes (?) No transcription errors! Streamlines workflow, increases efficiency 27

28 Stages of Medication Process Ordering Transcription Dispensing Administration CPOE Automatic Medication Dispensing Barcoded Medication Dispensing Electronic Medication Administration Records (e-mar) Barcoded Medication Administration 28

29 Clinical Decision Support Systems (CDS) The real place where most of the values of health IT can be achieved (Shortliffe, 1976) Expert systems Based on artificial intelligence, machine learning, rules, or statistics Examples: differential diagnoses, treatment options 29

30 Clinical Decision Support Systems (CDS) Alerts & reminders Based on specified logical conditions Examples: Drug-allergy checks Drug-drug interaction checks Reminders for preventive services Clinical practice guideline integration 30

31 Example of Reminders 31

32 More CDS Examples Reference information or evidencebased knowledge sources Drug reference databases Textbooks & journals Online literature (e.g. PubMed) Tools that help users easily access references (e.g. Infobuttons) 32

33 Infobuttons Image Source: 33

34 Other CDS Examples Pre-defined documents Order sets, personalized favorites Templates for clinical notes Checklists Forms Can be either computer-based or paper-based 34

35 Order Sets Image Source: 35

36 Other CDS Examples Simple UI designed to help clinical decision making Abnormal lab highlights Graphs/visualizations for lab results Filters & sorting functions 36

37 Abnormal Lab Highlights Image Source: 37

38 Clinical Decision Making PATIENT CLINICIAN Perception Attention Long Term Memory Knowledge Data Working Memory External Memory Knowledge Data Inference Elson, Faughnan & Connelly (1997) DECISION 38

39 Clinical Decision Making PATIENT CLINICIAN Perception Attention Abnormal lab highlights Long Term Memory Knowledge Data Working Memory External Memory Knowledge Data Inference DECISION 39

40 Clinical Decision Making PATIENT CLINICIAN Perception Attention Drug-Allergy Checks Long Term Memory Knowledge Data Working Memory External Memory Knowledge Data Inference DECISION 40

41 Clinical Decision Making PATIENT CLINICIAN Perception Attention Drug-Drug Interaction Checks Long Term Memory Knowledge Data Working Memory External Memory Knowledge Data Inference Elson, Faughnan & Connelly (1997) DECISION 41

42 Clinical Decision Making PATIENT CLINICIAN Perception Attention Clinical Practice Guideline Reminders Long Term Memory Knowledge Data Working Memory External Memory Knowledge Data Inference Elson, Faughnan & Connelly (1997) DECISION 42

43 Clinical Decision Making PATIENT CLINICIAN Perception Attention Long Term Memory Knowledge Data Working Memory External Memory Knowledge Data Elson, Faughnan & Connelly (1997) Inference DECISION Diagnostic/Treatment Expert Systems 43

44 Proper Roles of CDS CDSS as a replacement or supplement of clinicians? The demise of the Greek Oracle model (Miller & Masarie, 1990) The Greek Oracle Model Wrong Assumption The Fundamental Theorem Model Correct Assumption Friedman (2009) 44

45 Unintended Consequences of Health IT Some risks Alert fatigue 45

46 Workarounds 46

47 สถานการณ HIS/EHR (N=902) (นพ.นวนรรน ธ ระอ มพรพ นธ 2554) Product/Vendor Frequency (%) HOSxP 449 (50.17%) Self-developed or outsourced 142 (15.87%) Hospital OS 64 (7.15%) SSB 32 (3.58%) Mit-Net 22 (2.46%) MRecord 21 (2.35%) H.I.M. Professional 20 (2.23%) MedTrak/TrakCare 19 (2.12%) HoMC 18 (2.01%) No hospital information system used 14 (1.56%)

48 Health Information Exchange (HIE) Government Hospital A Hospital B Lab Patient at Home Clinic C 48

49 Outline Healthcare & Information Why We Need ICT in Healthcare Health IT Hospital Information Systems Health Information Exchange Q&A 49

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