The Surveillance Lab
E-Health Interventions in Public Health
 

Software Used

 
 
E-Health Interventions in Public Health

We all use information to make decisions. In our daily life, we have seen remarkable gains in the ease with which we can access information. Unfortunately, similar advances in information access have not occurred in public health practice, where it is often difficult to access necessary information. There is a huge potential benefit to society if we can develop and evaluate software to help people make better decisions about preventing chronic diseases, detecting infectious disease outbreaks, and planning the delivery of public health services. This research program will develop and evaluate innovative strategies that use modern computing to improve decisions about important public health problems.


Funded By

 

In Collaboration With

 
The Clinical Decision Support Lab
Medication Reconciliation: The RightRx Trial
 

Software Used

 
 
Medication Reconciliation: The RightRx Trial

Effective implementation of medication reconciliation is essential to reduce preventable adverse drug events occurring at the transitions between community and hospital care. More efficient and reliable methods of obtaining the community drug list are critical to improve hospital staff adherence to the medication reconciliation process and reduce unintended discrepancies in community and hospital medication at discharge. Community-based pharmacy records could be used, particularly if the hospital treatment team could automatically retrieve these records. Adherence to medication reconciliation at discharge will likely be improved by providing an automated order entry process that facilitates re-ordering of hospital and community-based medications at discharge. Moreover, the effectiveness of an electronic medication reconciliation module in reducing adverse drug events may be augmented by interventions to improve the successful transmission of treatment discontinuation and change orders to community-based pharmacists and physicians.


Funded By

 

In Collaboration With

 
The Surveillance Lab
Surveillance of Vaccination Opinions and Beliefs in Online Media
 

 
Surveillance of Vaccination Opinions and Beliefs in Online Media

The goal of this project is to develop methods for public health surveillance of opinions and beliefs about vaccination expressed in online media. In particular, we intend to automate the detection and classification of comments about the safety and effectiveness of vaccines. To develop these methods we are using a large sample of media reports from HealthMap’s Vaccine Intelligence Surveillance System. The automated methods will be evaluated against manual classification of the same reports. As we develop and evaluate our methods, we are also performing descriptive analyses to understand how the frequency of media reports containing comments about vaccines changes over time and space. This work will provide evidence to guide the use of online media surveillance and monitor vaccine opinions and beliefs.

 


Funded By

 

In Collaboration With

 
The Cancer Care Quality Lab
Predicting Adverse events in Seniors Undergoing Colon Cancer Surgery Using Administrative Data: a Novel Approach to Comprehensive Geriatric Assessment
 

 
Predicting Adverse events in Seniors Undergoing Colon Cancer Surgery Using Administrative Data: a Novel Approach to Comprehensive Geriatric Assessment

Older patients undergoing colon cancer surgery (CCS) are at risk for adverse events. Identifying high-risk patients prior to CCS can potentially reduce the burden of post-surgical complications by better tailoring perioperative care. Currently, healthcare providers may apply the risk metrics suitable for the general population; however, these may be inappropriate for older cancer patients. This study evaluates the feasibility of using administrative claims to accurately profile recent health service use as a tool in predicting severe postoperative complications (Clavien-Dindo grades III-V) in older patients undergoing colon cancer surgery.


The Clinical Decision Support Lab
Reducing Injuries from Medication-Related Falls by Generating Targeted Computerized Alerts for High Risk Patients within an Electronic Prescribing System
 

 
Reducing Injuries from Medication-Related Falls by Generating Targeted Computerized Alerts for High Risk Patients within an Electronic Prescribing System

Drug-related illness is the sixth leading cause of mortality. Preventable adverse drug events in ambulatory practice  are estimated to occur in 2% to 3% of patients treated per year, of which 58% are related to prescribing errors. Older adults are at higher risk of adverse events and medication-related fall injuries are the most common problem. Approximately 10% to 39% of falls are attributable to the inappropriate use of psychotropic drugs and are potentially preventable. The purpose of this research is to reduce medication-related fall injuries by using computerized electronic prescribing and drug management systems to identify high risk patients and provide physicians with patient-specific recommendations for modifying psychotropic medication use to reduce this risk. We will develop and test a “smart-alert” system for modifying high risk psychotropic drug use among high risk patients within the MOXXI system  to determine if the smart-alert system reduces the rate of inappropriate psychotropic drug prescriptions and fall-related injuries.


Funded By

 
The Clinical Decision Support Lab
Providing Comparative Out-of-Pocket Cost Information for Prescription Drugs through an Integrated Physician Electronic Prescribing System: A Proof of Concept with Anti-hypertensive Drugs

The potential benefits of new drug treatments and increased medication utilization rates have not been fully realized, even though the proportion of health costs due to drug expenditures continues to rise on a yearly basis. This has created a need to investigate new methods to maximize the benefits of existing and new drug treatments while minimizing costs. This research will build on initiatives to implement electronic prescribing and integrated drug management systems to improve patient safety. The study will assess a) whether access to detailed comparative information on patient out-of-pocket cost for drugs of equivalent effectiveness at the time of prescribing will improve the cost-effectiveness of drugs prescribed for uncomplicated hypertension and b) determine the impact on patient adherence with the anti-hypertensive therapy. The results will help to assess the degree to which evidence-based decision-support systems that provide physicians with information on out-of-pocket payments from patients can be integrated into electronic prescribing and integrated drug management systems and produce improvements in cost-effective prescribing.


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