Lesson 6

• Health Management Information System (HMIS)


  An information system specially designed to assist in the management and planning of health programs, as opposed to delivery of care
• HMIS


  • One of the six building blocks essential for health system strengthening
  • A data collection system specifically designed to support planning, management, and decision-making in health facilities and organizations
• HMIS


  A set of integrated components and procedures organized with the objective of generating information, which will improve health care management decisions at all levels of the health system<|>A routine-monitoring system that monitors and evaluates the process with the intention of providing warning signals through the use of indicators
• HMIS at the health unit level


  Used by the health unit in charge and the Health Unit Management Committee to plan and coordinate health care services in their catchment area
• Concepts HMIS was developed within


  • The information collected is relevant to the policies and goals of the healthcare institution, and to the responsibilities of the health professionals at the level of collection
  • The information collected is functional; it is to be used immediately for management and should not wait for feedback from higher levels
  • Information collection is integrated; there is one set of forms and no duplication of reporting
  • The information is collected on a routine basis from every health unit
• Role of HMIS


  To provide quality information to support decision-making at all levels of the health care system in any medical institution<|>To encourage the use of Health Information in hospitals<|>To aid in the setting of performance targets at all levels of health service delivery<|>To assist in assessing performance at all levels of the health sector
• Characteristics of a good HMIS

  • Complete - It should provide information on all key aspects of the health system without duplication
  • Consistent - If similar information is provided by different sources, their definitions need to be consistent
  • Clear - It should be very clear what all the elements are actually measuring
  • Simple - It should not be unnecessarily complicated
  • Cost-Effective - The actual usage of each element should justify the costs of its collection and analysis
  • Accessible - Data should be held in a form readily accessible to all legitimate users, and it should be clear who these people are
  • Confidential - It should ensure that people without legitimate access are effectively denied
• Fundamental information-processing phases of HMIS

  1. Data input - includes data acquisition and data verification

  2. Data management - includes data storage, data classification, data update, and data computation

  3. Data output - includes data retrieval and data presentation
• Elements of HMIS

  • Data Acquisition
  • Data Verification
  • Data Storage
  • Data Classification
  • Data Computation
  • Data Update
  • Data Retrieval
  • Data Presentation
• Data Acquisition


  Generation and collection of accurate, timely, and relevant data, normally achieved through the input of standard coded formats (e.g., the use of bar codes) to facilitate the rapid mechanical reading and capturing of data
• Data Verification


  Authentication and validation of gathered data. The quality of collected data depends largely on the authority, validity, and reliability of the data sources
• Data Storage


  Preservation and archival of data. When accumulated data are no longer actively used in the system, a method to archive the data for a certain period is usually advisable and may sometimes be mandatory, as when it is required by legislation
• Data Classification


  Also known as Data Organization. A critical function for increasing the efficiency of the system when the need arises to conduct a data search. Most data classification schemes are based on the use of certain key parameters, e.g., data referring to a patient population may be classified and sorted according to various diagnostic classification schemes
• Data Computation


  Various forms of data manipulation and data transformation, such as the use of mathematical models, statistical and probabilistic approaches, linear and nonlinear transformation, and other data analytic processes. It allows further data analysis, synthesis, and evaluation so that data can be used for strategic decision-making purposes other than tactical and/or operational use
• Data Update


  Accounting for new and changing information. The dynamic nature of such data modification calls for constant monitoring. For HMIS to maintain current data, mechanisms must be put in place for updating changes in the face of any ongoing manual or automated transactions
• Data Retrieval


  Concerned with the processes of data transfer and data distribution. The data transfer process is constrained by the time it takes to transmit the required data from the source to the appropriate end-user. One significant criterion to be considered in the data retrieval function is the economics of producing the needed information
• Data Presentation


  How users interpret the information produced by the system. In situations where only operational or even tactical managerial decision-making is expected, summary tables and statistical reports may suffice. The use of presentation graphics for higher-level managerial decision analysis is particularly encouraged because these appear to provide a better intuitive feel of data trend
• Data retrieval function


  Criterion to be considered is the economics of producing the needed information
• Data presentation


  How users interpret the information produced by the system
• Summary tables and statistical reports

  May suffice for operational or tactical managerial decision-making
• Presentation graphics


  Encouraged for higher-level managerial decision analysis as they provide a better intuitive feel of data trend
• Functions in HMIS

  • Client data
  • Client Billing Data
  • Client Clinical Data
  • Scheduling
  • Authorization Tracking
  • Billing
  • Accounts Receivable (A/R) Management
  • Reporting
  • Medical record
  • Compliance
  • Financial
  • Other Client Data
• Linking Schedule to Billing

  1. Authorized and Use of Authorized Units

  2. Complaint Electronic Claim

  3. Tracking Aging of Unpaid Services

  4. Tracking Reasons for Denials

  5. Aged Receivable Report by Payer Source
• Reporting

  • Basic Reports
  • Report Writer
• Client Clinical Data

  • Assessment
  • Treatment Plan
  • Progress/encounter Notes
  • Expired Treatment Plan
  • Service on Treatment Plan
  • Progress Note Present
• Financial

  • General Ledger
  • Payroll
  • Accounts Payable
  • Financial Reporting
• Determinants of HMIS performance

  • Behavioral
  • Organizational
  • Technical
• Behavioral determinants


  Data collector and users need confidence, motivation, and competence to perform HMIS tasks
• Lack of enough knowledge on the use of data has been found to be a major drawback on data quality and information use</b>
• Motivating HMIS users remains a challenge despite training on data collection and data analysis
• Organizational determinants

  • Finance
  • Supervision
  • Governance
  • Planning
  • Training
  • Quality
• Organizational culture is important to improve RHIS performance, promoting a culture of information use
• Technical determinants


  • Complexity of the reporting forms
  • Procedures set forward in the collection of data
  • Overall design of the computer software used in the collection of information
• Technical factors involve the overall design used in the collection of the information
• PRISM Framework


  Conceptual framework that broadens the analysis of routine health information systems to include behavioral, technical, and organizational/environmental determinants
• PRISM Framework identifies strengths and weaknesses and correlations among areas to design and prioritize interventions to improve RHIS performance
• Components of PRISM Framework

  • Technical Factors
  • Organizational Factors
  • Behavioral Factors
• PRISM Framework defines the components of the routine health information system and their linkages to produce better quality data and continuous use of information, leading to better health system performance and better health outcomes