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A patient registry is an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure, and that serves one or more stated scientific, clinical, or policy purposes.
- 2020/09
Oct 12, 2012 · A patient registry is an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure, and that serves one or more predetermined scientific, clinical, or policy purposes.
- 2014/04
The types of data to be collected are guided by the registry design and data collection methods. The form, organization, and timing of required data are important components in determining appropriate data sources.
- Richard E Gliklich, Nancy A Dreyer, Michelle B Leavy
- 2014/04
- 2014
- Ongoing
Sep 25, 2023 · Data collection is fundamental in today's healthcare, underpinning evidence-based decisions and enhancing patient care. Its role in delivering personalized treatments is transformative. For example, genomic data can pinpoint cancer treatments targeting specific mutations, elevating success rates.
- Anand Babu
- WHO TOOLKIT FOR ANALYSIS AND USE OF ROUTINE HEALTH FACILITY DATA
- Acknowledgements
- Abbreviations
- Guidance overview and references
- Learning objectives
- Audience
- Rationale for the toolkit
- Structure of the toolkit
- Part 1: Standards for measurement and analysis
- Part 2: Integrated health service analysis
- Part 3: Programme-specific guidance
- 1.2 Overview of routine health information systems
- The RHIS within the national health information system (HIS)
- Advantages of RHIS data
- Limitations of RHIS data
- DATA
- EVIDENCE
- 2. Core indicators
- Core indicator list
- Consistency with international standards
- Standardization of indicators and data elements
- 2.2 Core RHIS indicators
- 3.1 Representativeness versus completeness
- 3.2 Master Facility List (MFL)
- 4. Data quality
- 4.1 Types of data quality assessment
- Periodic assessments of tracer indicators
- Periodic in-depth programme-specific reviews
- 4.2 Dimensions of data quality assessment
- ▪ Assess completeness of reporting for each form
- ▪ Assess completeness of reporting for key data elements
- ▪ Consider completeness of reporting from hospitals and private sector facilities
- ▪ Assess the impact of incomplete reporting on coverage
- Dimension 2: Internal consistency of reported data
- ▪ Assess consistency between reported data and source documents
- Dimension 3: External consistency with other data sources
- Dimension 4: External comparison of population data
- 5.1 Census-based projections
- Subpopulations by region, 2012, United Republic of Tanzania (based on projections of 2002 national census)
- 6.2 Aggregated versus individual data
- 6.3 Disaggregation
- 6.4 Equity analysis
- 6.5 Comparisons with other data sources
- ▪ Population-based surveys
- ▪ Data from sentinel sites and demographic surveillance sites
- 7. Presentation and communication
- 7.4 Presenting a story
- 8.1 Interpretation of RHIS data
This document is part of the WHO Toolkit for analysis and use of routine health facility data – a set of capacity-building resources to optimize the analysis and use of data collected from health facilities through routine health information systems (RHIS). The toolkit is a collaborative effort by multiple WHO technical programmes and partners. I...
This General principles document from the Toolkit for analysis and use of routine health facility data has been developed by the World Health Organization (WHO), with the support of grants from Bloomberg Philanthropies Data for Health Initiative; Gavi, the Vaccine Alliance; The Global Fund to Fight AIDS, Tuberculosis and Malaria; and the Norwegian ...
ABER ACT ANC ART BCG CBR CRVS DHIS DHS DQR DTP EPI FBO HIS HIV HMIS IPTp LMIS MCV MFL MICS MR NGO OPV Penta RHIS RMNCAH RDT SD SOPs TB UHC USAID WHO annual blood examination rate artemisinin-based combination therapy antenatal care antiretroviral therapy bacille Calmette–Guérin (vaccine) crude birth rate civil registration and vital stati...
This document introduces the Toolkit for analysis and use of routine health facility data and provides an overview of key data analysis principles that are relevant to all the modules of the toolkit.
The guidance aims to promote understanding of: the concept of a standardized core indicator list; issues concerning health facility representation in routine health information systems (RHIS); key dimensions of data quality assessment; challenges related to population estimates and denominators for calculating indicators; basic analytical concepts,...
The guidance is relevant for workers in ministries of health and other organizations at various levels of the health system, including: decision-makers that use RHIS data for planning, management and review of health services; staff responsible for the analysis and presentation of health data, including analysts and monitoring and evaluation office...
Routine health facility data comprise data that are reported at regular intervals from facilities providing health services. The system of regular recording, reporting, analysis and presentation of health facility data is known as the routine health information system (RHIS).1 RHIS data provide a picture of the services delivered in health faciliti...
Refer to the inside front cover of this document for an illustration of the toolkit contents. The toolkit consists of three parts, each of which contains a number of modules. Each module contains a guidance manual(s) and may also contain downloadable electronic dashboard packages (“configuration packages”) and training materials.
This part provides foundations for analysis and use of RHIS data that are applicable across all the toolkit modules. It includes three modules: general principles, which discusses basic concepts for analysing RHIS data; core indicators, which includes the indicators from all the modules; and data quality assurance tools, which countries can use t...
This part contains two modules, targeting general health service planners and managers at national level and district and facility levels respectively. The modules provide an integrated (or cross-cutting) approach to analysis of health service performance, drawing on indicators from multiple toolkit modules.
This part contains programme-specific modules including: reproductive, maternal, newborn, child and adolescent health (RMNCAH); Expanded Programme on Immunization (EPI); human immunodeficiency virus (HIV); tuberculosis (TB); malaria; and hepatitis. Each of these modules contains a set of core indicators specific to the programme, addresses re...
As health workers go about their daily work of delivering care, they record data in health facility records such as individual patient records (e.g. antenatal cards), registers, tally sheets and log books. Selected data are extracted from these records, aggregated in tally sheets or counted from registers, and then consolidated in monthly paper-bas...
The RHIS is an integral part of the overall national HIS. HIS data sources are usually either population-based or institution-based. Population-based sources include population censuses, civil registration and vital statistics (CRVS) systems and population-based surveys. These sources relate to the entire population (i.e. not only to people using...
The RHIS is an established component of the health service delivery system, providing information on a wide range of services. It applies across the entire country, at all levels of the health system. RHIS data are collected by and can be analysed by the service providers themselves, providing them with insights into the outputs and outcomes of the...
Health facility data can provide information only on the people that use the facilities. However, substantial parts of the population may not have access to the facilities (e.g. nomadic or marginalized groups) or may choose to use alternate care options (e.g. self-medication, traditional healers). Furthermore, some facilities (notably private provi...
Data organization Quality checks Indicator calculation DECISIONS
Presentation Contextualization Interpretation The terms “data” and “information” often are used interchangeably. However, “data” refers to raw, unprocessed numbers or text, while “information” refers to data that have been processed, organized and presented within a specific context to give the data meaning. Selection of appropriate indicators an...
Analysis and use of routine health facility data can be strengthened by focusing on a limited, standardized set of core indicators.
core indicator list consists of a limited set of key indicators. The core RHIS indicator list focuses data analysis on the most important indicators needed on a regular basis to monitor health services and inform decisions at various levels of the health system. Establishment of the core indicator list should be collaborative process involving mult...
The core facility indicator list should include a balanced set of both general and programme-specific indicators that are consistent with international health service and programmatic standards and reporting requirements.
Well-defined, standardized indicators, data elements and metadata are essential. This avoids the creation of multiple similar but incompatible indicators and data elements and enables consistent analysis of data across programmes and partners and over time. A standard core indicator set also provides the basis for a set of standardized core analyse...
Each programme-specific guidance manual in the Toolkit for analysis and use of routine health facility data contains a list of recommended core indicators relevant to the programme. The Integrated health services analysis module includes general health services indicators (e.g. outpatient department attendance) as well as a selection of tracer indi...
Appropriate interpretation of RHIS data requires an understanding of the extent to which all the facilities in the country are included in the RHIS. Assessment of facility representation in the RHIS is different from assessment of reporting completeness, which measures whether the facilities that are already included in the RHIS have submitted repo...
An MFL is a complete, up-to-date, authoritative listing of the health facilities in a country, including public, private-for-profit, NGO, FBO and military facilities, etc. It is the primary source from which other facility lists in the country are drawn, and must be validated, continuously updated and accessible. The MFL includes the data needed to...
All data have limitations that affect their reliability and interpretation. Therefore, before further analysis and interpretation, RHIS data should be assessed for quality. Errors can be corrected through communications with districts or health facilities. Adjustments to the data, e.g. for incomplete reporting, can also be made by analysts. Any suc...
Assessment of the quality of routine facility data requires a multipronged approach that includes: routine, regular assessments (e.g. monthly); periodic assessments of a core set of tracer indicators (e.g. annual); and periodic in-depth programme-specific reviews.
Interpretation involves drawing conclusions from or “making sense of” the data. It entails understanding what the data mean within a specific context and in relation to other information, including the limitations of the data. Interpretation requires insights into the technical and management aspects of the health issues/services under review, as w...
Interpretation involves drawing conclusions from or “making sense of” the data. It entails understanding what the data mean within a specific context and in relation to other information, including the limitations of the data. Interpretation requires insights into the technical and management aspects of the health issues/services under review, as w...
Interpretation involves drawing conclusions from or “making sense of” the data. It entails understanding what the data mean within a specific context and in relation to other information, including the limitations of the data. Interpretation requires insights into the technical and management aspects of the health issues/services under review, as w...
Interpretation involves drawing conclusions from or “making sense of” the data. It entails understanding what the data mean within a specific context and in relation to other information, including the limitations of the data. Interpretation requires insights into the technical and management aspects of the health issues/services under review, as w...
Interpretation involves drawing conclusions from or “making sense of” the data. It entails understanding what the data mean within a specific context and in relation to other information, including the limitations of the data. Interpretation requires insights into the technical and management aspects of the health issues/services under review, as w...
Interpretation involves drawing conclusions from or “making sense of” the data. It entails understanding what the data mean within a specific context and in relation to other information, including the limitations of the data. Interpretation requires insights into the technical and management aspects of the health issues/services under review, as w...
Interpretation involves drawing conclusions from or “making sense of” the data. It entails understanding what the data mean within a specific context and in relation to other information, including the limitations of the data. Interpretation requires insights into the technical and management aspects of the health issues/services under review, as w...
Interpretation involves drawing conclusions from or “making sense of” the data. It entails understanding what the data mean within a specific context and in relation to other information, including the limitations of the data. Interpretation requires insights into the technical and management aspects of the health issues/services under review, as w...
Interpretation involves drawing conclusions from or “making sense of” the data. It entails understanding what the data mean within a specific context and in relation to other information, including the limitations of the data. Interpretation requires insights into the technical and management aspects of the health issues/services under review, as w...
Interpretation involves drawing conclusions from or “making sense of” the data. It entails understanding what the data mean within a specific context and in relation to other information, including the limitations of the data. Interpretation requires insights into the technical and management aspects of the health issues/services under review, as w...
Interpretation involves drawing conclusions from or “making sense of” the data. It entails understanding what the data mean within a specific context and in relation to other information, including the limitations of the data. Interpretation requires insights into the technical and management aspects of the health issues/services under review, as w...
Interpretation involves drawing conclusions from or “making sense of” the data. It entails understanding what the data mean within a specific context and in relation to other information, including the limitations of the data. Interpretation requires insights into the technical and management aspects of the health issues/services under review, as w...
Interpretation involves drawing conclusions from or “making sense of” the data. It entails understanding what the data mean within a specific context and in relation to other information, including the limitations of the data. Interpretation requires insights into the technical and management aspects of the health issues/services under review, as w...
Interpretation involves drawing conclusions from or “making sense of” the data. It entails understanding what the data mean within a specific context and in relation to other information, including the limitations of the data. Interpretation requires insights into the technical and management aspects of the health issues/services under review, as w...
Interpretation involves drawing conclusions from or “making sense of” the data. It entails understanding what the data mean within a specific context and in relation to other information, including the limitations of the data. Interpretation requires insights into the technical and management aspects of the health issues/services under review, as w...
Interpretation involves drawing conclusions from or “making sense of” the data. It entails understanding what the data mean within a specific context and in relation to other information, including the limitations of the data. Interpretation requires insights into the technical and management aspects of the health issues/services under review, as w...
Interpretation involves drawing conclusions from or “making sense of” the data. It entails understanding what the data mean within a specific context and in relation to other information, including the limitations of the data. Interpretation requires insights into the technical and management aspects of the health issues/services under review, as w...
Interpretation involves drawing conclusions from or “making sense of” the data. It entails understanding what the data mean within a specific context and in relation to other information, including the limitations of the data. Interpretation requires insights into the technical and management aspects of the health issues/services under review, as w...
Interpretation involves drawing conclusions from or “making sense of” the data. It entails understanding what the data mean within a specific context and in relation to other information, including the limitations of the data. Interpretation requires insights into the technical and management aspects of the health issues/services under review, as w...
Interpretation involves drawing conclusions from or “making sense of” the data. It entails understanding what the data mean within a specific context and in relation to other information, including the limitations of the data. Interpretation requires insights into the technical and management aspects of the health issues/services under review, as w...
Interpretation involves drawing conclusions from or “making sense of” the data. It entails understanding what the data mean within a specific context and in relation to other information, including the limitations of the data. Interpretation requires insights into the technical and management aspects of the health issues/services under review, as w...
Interpretation involves drawing conclusions from or “making sense of” the data. It entails understanding what the data mean within a specific context and in relation to other information, including the limitations of the data. Interpretation requires insights into the technical and management aspects of the health issues/services under review, as w...
Apr 19, 2020 · This reference book on applied statistics for hospitals was designed and developed to provide an elementary understanding of the terms, definitions, and formulae used in computing the...
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RHIS data provide a picture of the services delivered in health facilities and the health status of the people using the services. The data can be used to assess the performance of individual facilities and to assess service utilization and coverage of interventions in defined populations.
