Pervasive Developmental Disorders

PDD-NOS Module

PDD-NOS Module

PDD-NOS Module

Data

Data Collection
It summarizes information about the data sources needed to monitor &  evaluate the program.
The plan should include information for each data source such as:
• The timing and frequency of collection
• The person/agency responsible for the collection
• The information needed for the indicators
• Any additional information that will be obtained from the source

Data Quality
Data quality is important to consider when determining the usefulness of various data sources; the data collected are most useful when they are of the highest quality.
It is important to use the highest quality data that are obtainable, but this often requires a trade off with what it is feasible to obtain. The highest quality data are usually obtained through the triangulation of data from several sources. It is also important to remember that behavioral and motivational factors on the part of the people collecting and analyzing the data can also affect its quality.

Some types of errors or biases common in data collection include:
• Sampling bias: occurs when the sample taken to represent population values is not a representative sample
• Non-sampling error: all other kinds of measurement, such as courtesy bias, incomplete records, or non-response rates
• Subjective measurement: occurs when the data are influenced by the measure

Here are some data quality issues to consider:
• Coverage: Will the data cover all of the elements of interest?
• Completeness: Is there a complete set of data for each element of interest?
• Accuracy: Have the instruments been tested to ensure validity and reliability of the data?
• Frequency: Are the data collected as frequently as needed?
• Reporting Schedule: Do the available data reflect the time periods of interest?
• Accessibility: Are the data needed collectable/retrievable?
• Power: Is the sample size big enough to provide a stable estimate or detect change?

Data Use
The term data refers to raw, unprocessed information while information, or strategic information, usually refers to processed data or data presented in some sort of context.

Collecting data is only meaningful and worthwhile if it is subsequently used for evidence-based decision-making. To be useful, information must be based on quality data, and it also must be communicated effectively to policy makers and other interested stakeholders.
M&E data need to be manageable and timely, reliable, specific to the activities in question, and the results need to be well understood.

The key to effective data use involves linking the data to the decisions that need to be made and to those making these decisions.
The decision-maker needs to be aware of relevant information in order to make informed decisions.
When decision-makers understand the kinds of information that can be used to inform decisions and improve results, they are more likely to seek out and use this information.

Health Information Systems (HIS)

Health information systems refer to any system that captures, stores, manages or transmits information related to the health of individuals or the activities of organisations that work within the health sector. This definition incorporates things such as district level routine information systems, disease surveillance systems, and also includes laboratory information systems, hospital patient administration systems (PAS) and human resource management information systems (HRMIS). Overall, a well-functioning HIS is an integrated effort to collect, process, report and use health information and knowledge to influence policy and decision-making, programme action, individual and public health outcomes, and research. Sound decision-making at all levels of a health system requires reliable health statistics that are disaggregated by sex, age and socioeconomic characteristics. At a policy level, decisions informed by evidence contribute to more efficient resource allocation and, at the delivery level, information about the quality and effectiveness of services can contribute to better outcomes.

Information systems, particularly at lower levels of the health system (closer to the collection source), need to be simple and sustainable and not overburden health delivery staff or be too costly to run. Staff need feedback on how the routine data they collect can be used and also need to understand the importance of good quality data for improving health. Capacity building is required to ensure policymakers at all levels have the ability to use and interpret health data, whether it originates from routine systems, health surveys or special operational research. It is also important that health system staff understand the significance of local data for local program management, and that their needs for strengthened capacity for critical health statistical analysis are met. Local use of data collected at lower levels of the health system is a key step for improving overall data quality. Furthermore, aggregate patient information collected at various points of service delivery and made interoperable with routine HIS improves the quality and use of health information.

1.     Health Information Systems Resources

These include the legislative, regulatory and planning frameworks required for a fully functioning health information system, and the resources that are required for such a system to be functional. Such resources involve personnel, financing, logistics support, information and communications technology (ICT), and coordinating mechanisms within and between the six components

2.     Indicators

A core set of indicators and related targets is the basis for a health information system plan and strategy. Indicators need to encompass determinants of health; health system inputs, outputs and outcomes; and health status

3.     Data Sources

These can be divided into two main categories; (1) population-based approaches (censuses, civil registration and population surveys) and (2) institution-based data (individual records, service records and resource records). A number of data-collection approaches and sources do not fit into either of the above main categories but can provide important information that may not be available elsewhere. These include occasional health surveys, research, and information produced by community based organisations

4.     Data Management

This covers all aspects of data handling from collection, storage, quality-assurance and flow, to processing, compilation and analysis

5.     Information Products

Data must be transformed into information that will become the basis for evidence and knowledge to shape health action

6.     Dissemination and Use

  The value of health information is enhanced by making it readily accessible to decision-makers and by providing incentives for, or otherwise facilitating, information use.

Source taken from: http://phinnetwork.org/resources/health-information-systems-his/

Manfaat kayu manis

Manfaat kayu manis:

1. Mengatur gula darah

2. Mengurangi kadar kolesterol LDL/kolesterol berbahaya. mengurangi resiko penyakit kardiovaskular.

3. Memiliki senyawa anti infeksi alami. Kayu manis efektif terhadap H. pylori yaitu bakteri penyebab borok atau bisul dan patogen lainnya.

4. Mengurangi rasa sakit terkait dengan arthritis,

5. Mengurangi sitokin terkait dengan nyeri rematik.

6. Mengurangi proliferasi sel kanker, pencegahan kanker.

7. Mengandung serat, kalsium, zat besi, dan mangan

8. Zat kimia alami cinnamaldehyde, meningkatkan hormon progesteron dan menurunkan produksi testosteron pada wanita, menyeimbangkan hormon kesuburan.

9. Perawatan penyakit neurodegenerative (Alzheimer, Parkinson, multiple sclerosis, tumor otak, dan meningitis,

10. Mengurangi peradangan kronisn gangguan neurologis

11. Berpotensi efektif terhadap HIV4, sama dgn Cardiospermum helicacabum.

12. Mencegah penyakit jantung.

13. Menyehatkan pembuluh darah.

14. Mengurangi peradangan kronis

15. Mencegah Parkinson

16. Mengobati alzheimer

17. Mengobati tumor otak

18. Mengobati meningitis