INNOVATIONS IN DATA COLLECTION

Transcription

1 INNOVATIONS IN DATA COLLECTION Haiti PALS Johannesburg SEPTEMBER

2 THE PROBLEM SOLVING APPROACH SYSTEMS OBJECTIVES FEATURES OF TOOL SUPPORTED Aggregate Reporting Patient level data Case Notification & Surveillance Aggregate data for monitoring; reporting; performance measurement Patient level data allow providers to document patient care, look up care histories, share information Repository of unique cases for the sake of monitoring changes and identifying demographic and behavioral drivers epidemics. MESI : Web-based, (2004) Built by Local Firm Used by all HIV implementers; Monthly reports directly by sites EMR: Flexible approach to data entry (2005) In collaboration with University of Washington Seattle) SALVH/HASS Fed by the 3 EMR (2007) MESI: National Surveillance System Laboratory Information system Support the lab processes at site level OPENELIS : Web-based, Password protected Linked to the EMR for patient information 2

3 FRAMEWORK FOR SI INTERVENTIONS SYSTEM APPROACH HUMAN RESOURCES - STAFF (CENTRAL, DEPARTEMENTAL AND LOCAL LEVELS) - TRAINING DATA QUALITY AND USE - HEALTH QUAL - SURVEILLANCE (HIV, CHOLERA, MALARIA) TECHNOLOGY - NATIONAL SERVER - SITE INFRASTRUCTURES - APPLICATIONS TOOLS AND PROCESSES - FINANCING FOR FORMS AND REGISTERS - TASK FORCE FOR BACK LOGS - CLUSTERS GOVERNANCE & LOGISTICS - - PARTNERS FORUM 3

4 ISANTE: ELECTRONIC MEDICAL RECORD HIV Module started in 2005 to complement GHESKIO and PIH EMR Expansion to Primary Health Care in 2012 Used in Point of Care by majority of sites Provides reminders for critical services Provides patient summary Aggregates data across sites to examine health outcomes for: small population : patients, clinics, for large population : departments, national 4

5 Started in 2007 with case notification SALVH/HASS : CASE NOTIFICATION SYSTEM Data on treatment from all 3 EMR systems have been added progressively Large array of longitudinal data at the patient level Standardized procedure for automated data transfer Allow deduplication of data at the national level Analytic module recently added (SISENSE) allows advanced analysis 5

6 INNOVATIVE APPROACHES BIOMETRIC CODING AND MASTER PATIENT INDEX PLR AND COMMUNITY INTERVENTIONS PARTNER SERVICES HEALTH INFORMATION EXCHANGE 6

7 INTEGRATED INTERVENTIONS PLR & BC Program Built Upon Existing SALVH Pillars of intervention: SALVH: Longitudinal patient-level data from EMRs consolidated in SALVH A Master Patient Index using Biometric Code (BC) uniquely identify patients and ensure that every patient is represented only once, and with constant demographic identification PLR Gathers Geo-location Data for all patients 7

8 BIOMETRIC CODING AND MASTER PATIENT INDEX 8

9 BIOMETRIC CODING ARCHITECTURE Site Level MOH Level Local EMR server Consolidated servers Local FingerPrint server FP is added to local FP server upon registration into isanté FP data is replicated from local FP server to consolidated FP server 9

10 BIOMETRIC CODING OPERATIONS FP Registration Synchronization De-duplication 10

11 REGISTRATION PROCESS Search patient with FP Yes FP exists? No Load existing patient chart with existing FP Yes New patient? No Enrollment new patient follow-up visit for existing patients Data is stored using AES 128 bit encryption Add new record with FP Old fashion search Px Update existing record with its FP 11

12 DEDUPLICATION PROCESS Scheduled to happen at 2 levels Locally: already available one-to-many (1:N) No possibility to have duplicates FP Charts with no FP are either duplicates or LTFU Merging operation Nationally (across sites) Sites will have possibility to check names FROM National Server

13 The foundation is in place MASTER PATIENT INDEX (MPI) The MPI provides already a clear and complete view of individual patients with data on: Demographics (BC+GPS) Clinical Story Existing Duplicates DUPLICATES The MPIs will ensure that every patient is represented only once, and with constant demographic identification The Next step is to set up a registration system that restricts the possibility of creating duplicates 13

14 PATIENT RETENTION AND LINKAGE 14

15 PLR: THE FOUNDATION FOR COMMUNITY-BASED ACTIVITIES Use of tablets for patient visits Geo-location is at the center of the approach (30,705 patients) Allows Tracking of patients Lost to Follow up, Missing appointments, Lost before enrollment Allows Mapping of facilities and beneficiaries of interventions Support DAC Community-based drug distribution (15,231 patients) DASHBOARD FOR PATIENT LOST 15

16 INTEGRATION THROUGH HEALTH INFORMATION EXCHANGE 16

17 THE HEALTH INFORMATION EXCHANGE MODEL 17

18 Thanks 18