Difference between revisions of "Electronic health information exchange"

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== '''Electronic health information exchange''' ==
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'''Overview'''
  
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== '''Cox proportional hazards model''' ==
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Electronic health information exchange (HIE) offers a way for clinicians and organizations to electronically send and receive complete patient information between different facilities and systems that would normally not be able to communicate. HIE began at a time where technology, system standards, and health IT vendors used diverse and disconnected programs; creating a barrier to access patient records, health histories, and pertinent laboratory, radiology, and pathology results or orders. This was a significant deficit in quality of care, as it limited clinicians' ability to see the full picture and properly evaluate, assess, diagnose, and treat their patients. About 15 years ago, HIE began to transform into a more mature tool for care coordination, leading to the emergence of four primary roles of HIE(1):
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Cox regression, or sometimes referred to as proportional hazards regression, is a multivariate regression technique used to model survival analysis data.1 This technique is most commonly utilized when investigators are looking at time-to-event outcomes. Unlike other types of regression models, the only outcome reported for Cox regression is a hazard ratio. As a clinical informaticist, it is always a goal to improve patient outcomes. Cox regression is an invaluable tool to accomplish this. It allows the investigation of survival time of patients and the relationship to a series of continuous and/or binary predictors (covariates).
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1. ''Interconnectivity'' -- HIE tools help organizations avoid custom, point-to-point connections, where each provider must create a separate connection to every other system, service, and provider they want to communicate with
  
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'''Cox regression assumptions'''
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2. ''Clinical document exchange'' -- Efforts taken to ensure providers follow regulations that have established a minimum set of elements that providers should exchange to coordinate care; currently the "Continuity of Care Document (CCD)"
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• Proportional hazards assumption
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Cox regression is sometimes referred to as proportional hazards regression because it is required that the assumption of proportional hazards is met. Simply stated, the assumption states that the hazard ratio for any two individuals in the study needs to be constant over time. There are multiple ways to evaluate the proportional hazards assumption but below 4 are listed.
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1. Examine log(-log(S(t)) plots
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3. ''Creating a community health record'' -- Regional HIEs can consolidate a patient’s health information into a community health record, which is a more complete picture of the care a patient is receiving
  
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2. Include interaction with time in the model
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4. ''Encounter notifications'' -- HIE can be used to alert clinicians and other members of a patient's care team to make providers aware of recent encounters, health problems, emergency needs, etc. to ensure proper follow up and intervention is taken
  
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3. Plot Schoenfield residuals
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'''Advantages'''
  
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4. Regress Schoenfeld residuals against time to test for independence between residuals and time
 
  
  
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'''Statistical vocabulary'''
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'''Disadvantages'''
  
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• Schoenfeld residual – a separate residual for each individual for each covariate.2
 
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• Hazard ratio – an estimated ratio of hazard rates for the treated arm versus the control arm. A measure of how often an event happens in one group compared to how often the event occurs in another group, over time.3
 
 
   
 
   
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o HR > 1 indicates an increase in risk
 
  
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o HR < 1 indicates a decrease in risk
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'''Protocols & standards'''
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o HR = 0 indicates no change in risk
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'''History'''
 
  
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In 1972 Sir David Cox came out with his paper titled, “Regression Models and Life-Tables" outlining the proportional hazards model which was subsequently named after him.1 The model led to countless medical studies on survival time and various patient exposures/attributes such as age, diet, and drug exposure. He was knighted by Queen Elizabeth II in 1985.4
 
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'''Example'''
 
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Tyring S. et al. “Famciclovir for the treatment of acute herpes zoster: effects on acute disease and postherpetic neuralgia. A randomized, double-blind, placebo-controlled trial. Collaborative Famciclovir Herpes Zoster Study Group”. Ann Intern Med. 1995 Jul 15;123(2):89-96.
 
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o The study was using Cox Regression and hazard ratios to investigate the outcomes of a specific drug treatment regimen. This model is commonly used when determining the effects of a drug on disease prognosis while incorporating multiple other predictors into the model.
 
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'''Principle use'''
 
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Being able to identify variables that will influence the outcome of a patient’s prognosis is a critical role of all healthcare providers and clinical informaticists. Cox regression allows investigators to evaluate the effects of multiple predictors simultaneously and gain a better understanding of the effect size for each predictor. With the advent of EMR’s and dramatically increased access to data, healthcare providers can utilize Cox regression models to help guide therapies, clinical decision making, and prognostic criteria.
 
  
 
'''Sources'''  
 
'''Sources'''  
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<div class="csl-entry"><i>1. The Oregon Health Authority and Health IT: Health Information Exchange Overview</i>. (n.d.).</div>
  
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1. Cox, D. (1972). "Regression Models and Life-Tables". Journal of the Royal Statistical Society, Series B. 34 (2): 187–220.
 
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2. Schoenfeld D. (1982) Residuals for the proportional hazards regression model. Biometrika, 69(1):239-241.
 
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3. Spruance, Spotswood L et al. “Hazard ratio in clinical trials.” Antimicrobial agents and chemotherapy vol. 48,8 (2004): 2787-92. doi:10.1128/AAC.48.8.2787-2792.2004
 
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4. “No. 50221”. The London Gazette. 6 August 1985. P. 10815.
 
  
  
  
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Submitted by (Matthew Hill)
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Submitted by (LeeAnn Farestrand)
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[[Category:BMI512-SPRING-18]]
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[[Category:BMI512-SPRING-22]]

Revision as of 02:43, 26 April 2022

Electronic health information exchange

Overview

Electronic health information exchange (HIE) offers a way for clinicians and organizations to electronically send and receive complete patient information between different facilities and systems that would normally not be able to communicate. HIE began at a time where technology, system standards, and health IT vendors used diverse and disconnected programs; creating a barrier to access patient records, health histories, and pertinent laboratory, radiology, and pathology results or orders. This was a significant deficit in quality of care, as it limited clinicians' ability to see the full picture and properly evaluate, assess, diagnose, and treat their patients. About 15 years ago, HIE began to transform into a more mature tool for care coordination, leading to the emergence of four primary roles of HIE(1):

1. Interconnectivity -- HIE tools help organizations avoid custom, point-to-point connections, where each provider must create a separate connection to every other system, service, and provider they want to communicate with

2. Clinical document exchange -- Efforts taken to ensure providers follow regulations that have established a minimum set of elements that providers should exchange to coordinate care; currently the "Continuity of Care Document (CCD)"

3. Creating a community health record -- Regional HIEs can consolidate a patient’s health information into a community health record, which is a more complete picture of the care a patient is receiving

4. Encounter notifications -- HIE can be used to alert clinicians and other members of a patient's care team to make providers aware of recent encounters, health problems, emergency needs, etc. to ensure proper follow up and intervention is taken

Advantages


Disadvantages


Protocols & standards


Sources

1. The Oregon Health Authority and Health IT: Health Information Exchange Overview. (n.d.).



Submitted by (LeeAnn Farestrand)

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