UM MPH MBQ7046 - Data Collection and Standards in HIMS PDF

Data collection and Standards in HIMS Modeling Public Health Data MBQ7046 (1) Program Sarjana Kesihatan Awam (MPH), UM Dr. ‘Ismat Mohd Sulaiman (MD, MSc HI, PhD candidate PHI) Health Informatics Centre, Planning Division, MOH Malaysia 6 June 2024, 1000 - 1300 Data collection and Standards - Dr. '...

Data collection and Standards in HIMS Modeling Public Health Data MBQ7046 (1) Program Sarjana Kesihatan Awam (MPH), UM Dr. ‘Ismat Mohd Sulaiman (MD, MSc HI, PhD candidate PHI) Health Informatics Centre, Planning Division, MOH Malaysia 6 June 2024, 1000 - 1300 Data collection and Standards - Dr. 'Ismat Mohd Sulaiman STUDY OBJECTIVES 1. Able to discuss the development of health information systems in various healthcare settings. 2. Able to discuss the rationale behind the development of health information systems. 3. Able to discuss the use and implementation of health information systems in future healthcare planning. 4. Able to discuss issues in health information systems. 5. Able to discuss the evaluation of health information systems. 6. Knows how data for health information systems are collected. 2 Data collection and Standards - Dr. 'Ismat Mohd Sulaiman 1. Data in Healthcare 2. Data Management TOPICS 3. Data and Information Governance 4. Health Informatics Standards 3 Data collection and Standards - Dr. 'Ismat Mohd Sulaiman 1. DATA IN HEALTHCARE 1. Structured & Unstructured Data 2. Primary use data vs Secondary use data 3. Data-Driven vs Business-Driven approach 4 Data collection and Standards - Dr. 'Ismat Mohd Sulaiman Structured 2 categories of (20%) data Patient Registration Vital statistics Billing Which one is BETTER? Disease Registries Research (mostly) Better for WHAT? Unstructured How to ANALYSE (80%) Narrative text unstructured data? Imaging Sound Pattern Sensor 5 Data collection and Standards - Dr. 'Ismat Mohd Sulaiman 2 types of Health Data Usage PRIMARY DATA USE SECONDARY DATA USE * Not equivalent to Primary Data and Secondary Data 6 Data collection and Standards - Dr. 'Ismat Mohd Sulaiman Approach to designing information system Business-Driven Data-Driven ▪ Top-down implementation approach ▪ Bottom-up implementation approach ▪ Begins with understanding the business ▪ Begins with a specific question process and entities ▪ Data mart is developed to answer those ▪ Data mart is developed for each entity questions ▪ Often needs to collect more data ▪ Utilise existing / available data ▪ Huge exercise to begin because need to ▪ Faster to begin generating report, but cover large aspect of the business before harder to manage as more information generating reports model gets bigger ▪ Data warehouse concept: Inmon ▪ Data warehouse concept: Kimball 7 Data collection and Standards - Dr. 'Ismat Mohd Sulaiman Data manager Data analysts Data scientist Monitor data submission Data manager skills Data analysts skills Understands the business needs Computer coding +/- Receive & collate data Statistical skills Turn data into insightful information May be able to handle Clean data Prepare and present both structured and information unstructured data …Health informatician? 8 Data collection and Standards - Dr. 'Ismat Mohd Sulaiman 2. DATA MANAGEMENT 1. Software development cycle 2. Information system monitoring 3. Output 9  Data collection and Standards - Dr. 'Ismat Mohd Sulaiman Software development lifecycle for HIMS - EVERYTHING BEGINS WITH A QUESTION - What question needs to be answered? Q&A What are the information needed to answer the question? What are the variables (data element) to generate the information? Reinforce Feedback What is the availability / accessibility to the data? Plan & Develop Deploy & Define the system roadshow Design Testing & Maintain Available data: Where to get the data? Who manages the data? How Evaluation to get the data? What systems are in place? System Data Information Non-available data: Where to collect the data? How to collect the data? Operating Quantity Meaningful Front-end design: Interface (UI/UX), usability Used / Usability Quality Action- oriented 10 Back-end design: Conceptual model, Logical Model, Physical Model (Infrastructure), Data flow, Database Data collection and Standards - Dr. 'Ismat Mohd Sulaiman Data management https://www.dama.org/cpages/bo dy-of-knowledge Data Management Body of Knowledge (DMBoK) DAMA. Earley, S., & Henderson, D., Sebastian-Coleman, L (Eds.). The DAMA Guide to the Data Management Body of Knowledge (DAMA- DM BOK). Bradley Beach, NJ: Technics Publications, LLC. 2017. 11 Data collection and Standards - Dr. 'Ismat Mohd Sulaiman Information System Monitoring (as data managers) Data Quantity Data Quality Harmonize Data Cleaning Optimize Monitor Data profiling Verification at Duplication Apply validation submission Frequency different level Logic rules Timeliness: Range e.g. State to verify, Using tools or Apply Establish cut-off Programme to Logic approve rules constraints dates Create / enforce e.g. Operational unit Consistency standards → District → State Validation → PIK 12  PRACTICAL SESSION : Data collection and Standards - Dr. 'Ismat Mohd Sulaiman WHERE CAN YOU SPREAD THE Output INFORMATION? Publicize & Disseminate Final Harmonization Data Analysis Business Intelligence Tools 13 Data collection and Standards - Dr. 'Ismat Mohd Sulaiman Challenges Data manipulation and audit trail Data Integrity Collect granular data Data cleaning methodology Data Privacy Data Scrambling Technique ISO TC 215 on Health Informatics Data Security User Access Control Policy Refer MAMPU, Telehealth Data Governance Impartiality Conflict of Interest 14 Data collection and Standards - Dr. 'Ismat Mohd Sulaiman 3. DATA & INFORMATION GOVERNANCE “To enable access and usage to quality (healthcare) data and information in a secured way while maintaining the privacy and confidentiality of the individuals or organizations.” 15 Data collection and Standards - Dr. 'Ismat Mohd Sulaiman Data & Information Governance Who can access The processes To ensure the To ensure What, When, and to ensure system is privacy & Where quality secured confidentiality ✓User matrix ✓Master Data Management ✓Security standards ✓Informed consent ✓Data classification ✓Monitoring and evaluation ✓Security Poster ✓Health Information Assessment (SPA) framework (data collection, retention, use/output, sharing) 1. Access & 2. Data Quality 3. Privacy & 3. Security Usage & Integrity Ethics 16 Data collection and Standards - Dr. 'Ismat Mohd Sulaiman Accuracy DATA QUALITY Validity Completeness DIMENSIONS (In MyHDW) Consistency / Relevance Reliability Currency / Timeliness 17 Data collection and Standards - Dr. 'Ismat Mohd Sulaiman COMPONENT QUESTION 1. Is there a committee that oversees the DIG? Is it 1) GENERAL independent or comprehensive are its members? Establishing Data & 2. 1. Is there a venue to discuss issues related to DIG? Is there a user access control policy used? Information 2) ACCESS 2. 3. Does it adhere to the policy? Is there a user access matrix? Governance 4. Is there a clear roles and responsibilities for the different types of users? 1. Is there a policy and guideline on using the data stored? Comittee 3) USAGE 2. Is there a policy and guideline on using the information produced? 3. Is there an appointment person for managing data and ACCESS information requests? 1. Is there a policy and guideline on ensuring the privacy & DATA confidentiality of the data? QUALITY USAGE 4) PRIVACY 2. How do you ensure the privacy and confidentiality of the DATA & data? INFORMATION 1. What security standards used? GOVERNANCE COMMITTEE 5) SECURITY 2. How is the system accessed? What are the applicable (DIGC) security measures for such system? 1. How is the consent taken for data collection, data CONSENT PRIVACY 6) CONSENT processing and analysis, and information publication? 2. Is there a consent policy and guideline? 1. Is there an audit or method to assess data quality? SECURITY 7) DATA QUALITY 2. Is there a process to improve data quality? 18 3. Is there a program to ensure data quality? Data collection and Standards - Dr. 'Ismat Mohd Sulaiman DISCUSS: Who owns health data? 19 Data collection and Standards - Dr. 'Ismat Mohd Sulaiman DISCUSS: Would you allow data sharing? 20 Data collection and Standards - Dr. 'Ismat Mohd Sulaiman 4. HEALTH INFORMATICS STANDARDS 1. 4 types of Interoperability 2. Example of Semantic Standards 3. Discussion: application and use benefit 21 Data collection and Standards - Dr. 'Ismat Mohd Sulaiman INTEROPERABILITY “The ability of two or more systems or components to exchange information and to use the information that has been exchanged” (IEEE) 1. Technical interoperability:...is usually associated with hardware/software components, systems and platforms that enable machine-to- machine communication to take place. This kind of interoperability is often centered on (communication) protocols and the infrastructure needed for those protocols to operate. 2. Syntactic interoperability:...is usually associated with data formats. Certainly, the messages transferred by communication protocols need to have a well-defined syntax and encoding, even if it is only in the form of bit tables. However, many protocols carry data or content, and this can be represented using high-level transfer syntaxes such as HTML, XML. 3. Semantic interoperability:...is concerned with ensuring that the precise meaning of exchanged information is understandable by any other application that was not initially developed for this purpose. Semantic interoperability enables systems to combine received information with other information resources and to process it in a meaningful manner 4. Organisational interoperability: … the ability of organizations to effectively communicate and transfer (meaningful) data (information) even though they may be using a variety of different information systems over widely different infrastructures, possibly across different geographic regions and cultures. Organizational interoperability depends on successful technical, syntactical and semantic interoperability 22  Variable Data collection and Standards - Dr. 'Ismat Mohd Sulaiman Organi Interpretation Diagnosis Patient_Name No_ID Discipline ESR sation value Diabetic Type 2 DM with KKM Tipah 1234 35 High ESR medicine hypoglycaemia Internal DM type 2 with KKM Zainab 5657 Raised ESR Value 53 Medicine hypoglycemia ESR above General T2DM with KKM Mastura 0987 67 reference medicine hypoglycemia range MyHDD/DDSA defines the variable and values, and determines the properties of each variable and its values. Properties includes naming convention, data type, field size e.g: Patient name is defined as name of patient as per MyKad/other identification document. Data type is alphanumeric, field size 225 23 Data collection and Standards - Dr. 'Ismat Mohd Sulaiman Organi Interpretation Diagnosis Patient_Name No_ID Discipline ESR sation value Diabetic Type 2 DM with KKM Tipah 1234 35 High ESR medicine hypoglycaemia Internal DM type 2 with KKM Zainab 5657 53 Raised ESR Medicine hypoglycemia ESR above General T2DM with KKM Mastura 0987 67 reference medicine hypoglycemia range Malaysia Health Reference Data Model (MyHRDM) is a data model that defines key concepts used across organizations and illustrates the relationship between these concepts to enable a more precise way to store data and efficient way to build reports. Eg: ORGANISATION: A social unit of PERSONs that is structured and managed to meet a need or pursue a collective goal DISCIPLINE: A SPECIALTY delivered through an 24 ORGANISATION SPECIALTY: A specialised medical area which a Data collection and Standards - Dr. 'Ismat Mohd Sulaiman Concepts Definition Client A PERSON who receives health service Provider A PERSON who has delivered, is delivering, or has the potential to deliver health care, related services or goods Encounter An interaction between a CLIENT and one or more PROVIDERS Visit An interaction between a Client and one or more SERVICES Service A grouping or collection of healthcare activities delivered directly or indirectly through an ORGANISATION to a CLIENT Organisation A social unit of PERSONs that is structured and managed to meet a need or pursue a collective goal Discipline A SPECIALTY delivered through an ORGANISATION Specialty A specialised medical area which a PROVIDER is gazetted to practise. 25 Data collection and Standards - Dr. 'Ismat Mohd Sulaiman Organi Interpretation Diagnosis Patient_Name No_ID Discipline ESR sation value Diabetic Type 2 DM with KKM Tipah 1234 35 High ESR medicine hypoglycaemia Internal DM type 2 with KKM Zainab 5657 53 Raised ESR Medicine hypoglycemia ESR above General T2DM with KKM Mastura 0987 67 reference medicine hypoglycemia range E11.9 Type 2 diabetes mellitus without complications International Statistical Classification of Diseases and Related Health Problems (ICD) classifies the uniformed meaning for statistical analysis. 26 Each condition is mutually exclusive. Data collection and Standards - Dr. 'Ismat Mohd Sulaiman Documentation of diagnosis: Diabetes mellitus Written Diagnosis Code 3 Digit Code 4 Digit Hypoglycaemia E16 E16.2 Diabetes Mellitus with E14 E14.9 hypoglycaemia Uncontrolled DM E10 E10.9 Uncontrolled Diabetes E11 E11.6 Mellitus Type 2 with Hypoglycaemia Oral Hypoglycaemic Agents Y42 Y42.3 27 Data collection and Standards - Dr. 'Ismat Mohd Sulaiman Documentation of diagnosis: Thyroid carcinoma Written Diagnosis Code 3 Digit Code 4 Digit To rule out carcinoma Z03 Z03.1 Multinodular goitre To rule out E04 E04.2 Carcinoma Toxic multinodular goitre to rule E05 E05.2 out carcinoma Papillary Carcinoma M8050/3 – Morphology code Carcinoma in situ of thyroid gland D09 D09.3 Advanced Carcinoma of thyroid C73 C73 gland Papillary Carcinoma of Thyroid C73 C73 (M8050/3) gland with metastases to C79 C79.8 (M8050/6) parathyroid gland 28 Data collection and Standards - Dr. 'Ismat Mohd Sulaiman Organi ESR Interpretation Patient_Name No_ID Discipline Diagnosis sation [30341- value 2] Diabetic Type 2 DM KKM Tipah 1234 35 High ESR medicine with hypoglycaemia Internal DM type 2 KKM Zainab 5657 53 Raised ESR Medicine with hypoglycemia ESR above General T2DM with KKM Mastura 0987 67 reference medicine hypoglycemia range SNOMED CT 1. Uniforms terms with the same meaning into a single concept & code. Eg: 165468009 | Erythrocyte sedimentation rate raised (finding) | 2. Defines the relationship between different concepts. Eg: 394733009 |Medical specialty (qualifier value)| 29 Data collection and Standards - Dr. 'Ismat Mohd Sulaiman Variable Organis ESR Interpretation Patient_Name No_ID Discipline Diagnosis ation [30341- value 2] Type 2 DM with KKM Tipah 1234 Diabetic 35 High ESR hypoglycaemia medicine KKM Zainab 5657 Internal 53 Raised ESR DM type 2 with Value Medicine hypoglycemia ESR above KKM Mastura 0987 General 67 T2DM with reference range medicine hypoglycemia E11.9 Type 2 diabetes mellitus without complications MyHRDM 30 Data collection and Standards - Dr. 'Ismat Mohd Sulaiman References 1. Hersh, W. R., & Hoyt, R. E. (2018). Health informatics: Practical guide (7th ed.) (eBook ISBN:978-1-387-82750-3) 2. J. Rowley (2007).The wisdom hierarchy: representations of the DIKW hierarchy J Inf Sci, 33. 3. HIMS Blueprint, MoH Malaysia (2005) 4. Selvaraju, Datin Dr S. (2006)."Health information management: Malaysian experience." Health Informatics Center, MoH Malaysia 5. Sarrassat, et.al.,. (2018). Estimating drowning mortality in Tanzania: A systematic review andmeta-analysis of existing data sources. Injury Prevention. 25. injuryprev- 2018.10.1136/injuryprev-2018-042939. 6. World Economic Forum (2019) Health and Healthcare in the Fourth Industrial Revolution:Global Future Council on the Future of Health and Healthcare 2016-2018 Acknowledgement 1. Health Informatics Centre staff – past & present 31  Dr. ‘Ismat Mohd Sulaiman Thank you Senior Principal Assistant Director / Medical Officer Health Informatics Centre, Planning Division, MOH Malaysia [email protected] | +60162528651 https://www.linkedin.com/in/drismat/ Data collection and Standards - Dr. 'Ismat Mohd Sulaiman 32