Presenters: 

Milisa K Rizer, MD, MPH, FAAFP, FHIMSS, CPHIMS

Chief Clinical Information Officer Professor of Family Medicine, Nursing, & Biomedical Informatics

The Ohio State University Wexner Medical Center
 

Thomas Bentley, RN, MS, FHIMSS, CPHIMS, CHCIO 

Deputy CIO

Objectives: 

• Identify the top three factors that improve user efficiency and satisfaction.
• Identify the top tools that can be used to improve the amount of time spent in documentation activities. 
• Identify the two areas of greatest frustration of users of EMRs.
• Identify one area where your staff can be used to help with provider efficiency.
• Identify one place where you can be involved with improving the EMR in your hospital or clinic. 

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Many healthcare provider organizations recognize that implementing effective data governance is critical to meet increasing demand for information to support valuebased care and population health. However, they often find that achieving success in data governance is easier said than done. What is it about healthcare that makes data governance so challenging? What can organizations do to remove these barriers to consistent, timely, actionable information?

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The history of benefits paid to U.S. Military Veterans is actually as old as the Declaration of Independence. The Continental Congress approved the nation’s first pension law in 1776, granting half-pay for life to Revolutionary War Veterans in cases of loss of limb or other serious disability. 

The first national effort to provide disabled Veterans with medical care began with the opening of the Naval Home in Philadelphia in 1812, followed by the Soldiers’ Home in 1853 and St. Elizabeth’s Hospital in 1855 – both in Washington, D.C.
 

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According to Accenture analysis, when combined, key clinical health AI applications can potentially create $150 billion in annual savings for the United States healthcare economy by 2026.

At hyper-speed, AI is re-wiring our modern conception of healthcare delivery. AI in health represents a collection of multiple technologies enabling machines to sense, comprehend, act and learn1, so they can perform administrative and clinical healthcare functions.

Unlike legacy technologies that are only algorithms / tools that complement a human, health AI today can truly augment human activity—taking over tasks that range from medical imaging to risk analysis to diagnosing health conditions.

15 minutes. That’s how long your doctor has to see you, assess your complaint, diagnose a solution and see you out the door – hopefully on the pathway back to wellness.
This isn’t much time, when you consider the wealth of information that he or she has to consider. Your patient record, the medical research relevant to your complaint, the answers about your condition that you provide, the basic examination (“say aaaaaaah”) that is carried out.

So how will your doctor cope when faced with the tsunami of healthcare information that will occur when it is routine for your patient record to include data about your genome, your microbiome (bugs in your body) and your fitness regime?

Your electronic health record is fast becoming the most powerful tool in the medical toolkit. All the information will be stored in the cloud. It will have to be because the size of the electronic file containing your complete patient record is estimated to be as much as six terabytes. That’s a quarter of the whole of Wikipedia (24Tbs)!

A data file that large is required to enable the practice of precision medicine. This a new revolution in healthcare. It is the ability to target healthcare treatment specifically for an individual.

In addition to improving health outcomes, precision medicine will save vital health dollars because it is enabled by unique data insights that lead to more targeted treatments.

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LifeWIRE Improves Patient Engagement at the VA

Many veterans have chronic conditions or other considerations that require additional support outside the realm of traditional care.  Tele-health is a mechanism that can help fill this need.  Goals include improving engagement, producing more patient-centered data and care, addressing problems before they escalate, improving resource use, increasing efficiency and value, and ultimately saving lives.  LifeWIRE is a patient engagement tool that uses automated dialogue to help meet these goals successfully.  

Best Practices         

• Outreach - LifeWIRE checks in with patients, an especially useful aspect for those with chronic conditions
• Follow-up - Reminder messages can assist with medication adherence, follow up appointments, and other patient tasks
• Feedback - Can check on medication and patient satisfaction
• Automation - Automated dialogue means that no APP is required
• Integration - Quantitative data can be combined with qualitative data
• Versatility - The program can be used on any device (400+ wearable medical devices are compatible) and any media
• Security - Data is cloud based and secure

Impact of Telemedicine on Mortality, Length of Stay, and Cost Among Patients in Progressive Care Units: Experience From a Large Healthcare System

Although there are many studies about the effects of telemedicine in ICU, currently there are no studies on the effects of telemedicine in progressive care unit settings. Our study showed that TPCU intervention significantly decreased mortality in progressive care unit and hospital and progressive care unit length of stay despite the fact patients in TPCU were older and had higher disease severity, and risk of mortality. Increased postprogressive care unit hospital length of stay and total mean direct costs inclusive of telemedicine costs coincided with improved survival rates. Telemedicine intervention decreased overall mortality and length of stay within progressive care units without substantial cost incurrences. 

The full article can be viewed below.

Abstract

Importance: Patients with cancer who die soon after starting chemotherapy incur costs of treatment without the benefits. Accurately predicting mortality risk before administering chemotherapy is important, but few patient data–driven tools exist.

Objective: To create and validate a machine learning model that predicts mortality in a general oncology cohort starting new chemotherapy, using only data available before the first day of treatment.
 

Healthcare stakeholders are seeking new strategies to improve access to care, address disease management, and spur treatment innovation as a growing number of patients require higher quality, more complex care at lower costs. At a time when the number of people with chronic conditions continues to rise at a staggering rate, providers must manage more patients with the same number of resources, or less, and deploy technology that improves efficiency and effectiveness.

The healthcare industry is deeply vested in identifying new ways to improve the overall health and satisfaction of patients. As a result, provider organizations are adopting remote patient monitoring (RPM) services – inclusive of data from home health devices – as a new standard of care.

This report from eHealth Initiative (eHI) in partnership with Validic analyzes the driving market trends and subsequent barriers for the adoption of patient-generated health data (PGHD) as part of remote care programs. The report delves deep into the financial, operational, and clinical returns on investing in such initiatives – offering perspectives from providers, technologists, regulators, and even a patient enrolled in such a program.