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Data Collection II

Data Collection II

The nursing history captures and records the patient's health status, so that a care plan evolves to meet the patient's individual needs. The nursing health history is a part of the initial assessment. A comprehensive history covers all health dimensions and plays a significant role in the assessment process. A comprehensive history includes the patient's biographical information, reasons for seeking health care, expectations, present and past health history, medications, and...

Data Collection III

Data Collection III

The physical assessment examines the patient for objective data that defines the patient's condition, and aids in formulating the nursing care plan. The purpose of physical assessment is a health status appraisal, which includes identifying health problems, and establishing a database for nursing intervention.
The principles to begin the physical assessment include conducting a comprehensive or problem-related history in a quiet, well-lit room, emphasizing privacy and comfort for the...

Types of Reports II: Incident or Occurrence Report

Types of Reports II: Incident or Occurrence Report

An Incident or Occurrence Report in a healthcare setting is a crucial document used to record any unexpected occurrence that may or may not have affected a patient, employee, or visitor. Such reports are critical to improving patient safety and include all details leading up to and including the event.
Purposes:
In the healthcare industry, reports play a crucial role in documenting incidents within an agency. The primary objective of these reports is to ensure patient safety, uphold the...

Data Collection I

Data Collection I

Data collection gathers information needed to make accurate judgments about a patient's present condition. During a health history interview, subjective data is collected from the patient, their caregivers, or family members, and objective data is collected through observations and physical assessment. Patients are the primary source of subjective data. Thus information gathered from patients through interviews, observations, and physical examination is primary data. Secondary sources of...

Data Collection by Experiments

Data Collection by Experiments

Data collection is a systematic method of obtaining, observing, measuring, and analyzing accurate information. An experimental study is a standard method of data collection that involves the manipulation of the samples by applying some form of treatment prior to data collection. It refers to manipulating one variable to determine its changes on another variable. The sample subjected to treatment is known as “experimental units.”
An example of the experimental method is a public...

Types of Records II: Educational and Administrative Records

Types of Records II: Educational and Administrative Records

Maintaining nurses' educational and administrative records in healthcare settings, including hospitals and nursing schools, is paramount. Here's a breakdown of the types of academic records mentioned:

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Related Experiment Video

Updated: Aug 25, 2025

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

Practice Expense Data Collection and Methodology: Phase II Final Report.

Lane F Burgette, Joachim O Hero, Jodi L Liu

Rand Health Quarterly

|October 14, 2022

Summary

This summary is machine-generated.

Medicare practice expense (PE) payments rely on outdated 2006 data. This study explores updating PE rate-setting methodology through surveys, stakeholder feedback, and new data collection strategies for accurate resource allocation.

Keywords:

Health Care Costs Health Care Facilities Health Care Organization and Administration Health Care Payment Approaches Medicare Survey Research Methodology

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The Participant-Reported Implementation Update and Score PRIUS: A Novel Method for Capturing Implementation-Related Data Over Time

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Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

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Visualizing Field Data Collection Procedures of Exposure and Biomarker Assessments for the Household Air Pollution Intervention Network Trial in India

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The Participant-Reported Implementation Update and Score PRIUS: A Novel Method for Capturing Implementation-Related Data Over Time

The Participant-Reported Implementation Update and Score PRIUS: A Novel Method for Capturing Implementation-Related Data Over Time

Published on: February 19, 2021

Area of Science:

Health economics
Healthcare policy
Medical practice management

Background:

Medicare allocates billions for practice expense (PE) based on 2006 Physician Practice Information (PPI) Survey data.
Outdated data may lead to inaccurate PE payments, not reflecting current resource needs in healthcare.
Significant economic and healthcare system changes since 2006 necessitate data updates.

Purpose of the Study:

To evaluate methods for improving Medicare's PE rate-setting methodology.
To explore strategies for updating the data informing PE rates.
To address concerns regarding the accuracy of current PE payment calculations.

Main Methods:

Analysis of survey-based approaches for PE data collection.
Description of a lean model survey instrument.
Consideration of inter-agency data collection partnerships.
Review of stakeholder feedback from a June 2021 virtual town hall meeting.

Main Results:

Survey-based approaches are identified as the optimal method for data collection.
Advantages and disadvantages of different survey strategies were examined.
Stakeholder input was gathered on PE data collection and rate-setting processes.

Conclusions:

Updating PE rate-setting requires a comprehensive approach, considering various data collection and methodological improvements.
Recommendations for near- and longer-term changes to the CMS PE system are provided.
Continuous evaluation and adaptation of PE data and methods are crucial for accurate Medicare payments.