Machines Treating Patients? It's Already Happening

Looking back, many experts agree that the spotty record of early applications of AI don’t necessarily signal the demise of machine learning in medicine. Instead, they highlight the need to be humble with any innovation, especially one that comes with too much hype. “IBM was too ambitious in my opinion,” says Dr. Steve Jiang, director of the medical AI and automation lab at UT Southwestern.

Today’s efforts in AI are somewhat less flashy, though still potentially revolutionary, and all seem to recognize one vital lesson: treating patients is both art and science. Rather than attempting to replace the physicians in medical practice, AI can, and should, say more experts, become a valuable tool in enhancing what doctors do.

The full Time article can be viewed at this link.  

Data sharing practices of medicines related apps and the mobile ecosystem: traffic, content, and network analysis

Developers of mobile applications (apps) routinely, and legally, share user data. Most health apps fail to provide privacy assurances or transparency around data sharing practices. User data collected from apps providing medicines information or support may be particularly attractive to cybercriminals or commercial data brokers.

Medicines related apps, which collect sensitive and personal health data, share user data within the mobile ecosystem in much the same way as other types of apps. A small number of companies have the potential to aggregate and perhaps reidentify user data owing to their network position.

The full article can be downloaded below.  

Death by a Thousand Clicks: Where Electronic Health Records Went Wrong

The U.S. government claimed that turning American medical charts into electronic records would make health care better, safer, and cheaper. Ten years and $36 billion later, the system is an unholy mess: Inside a digital revolution gone wrong. A joint investigation by Fortune and Kaiser Health News.

The full Fortune article can be read at this link.  

Electronic Health Records: A Promising New Way To Fight the Opioid Epidemic

From the injured athlete who underwent ACL surgery to the mother recovering from a broken ankle, the nation’s opioid epidemic selects its victims indiscriminately and at an alarming rate, with 8% to 12% of patients prescribed painkillers eventually developing a use disorder. As of 2017 – the most recent full year for which data is available – prescribing rates still hover around 60 prescriptions per 100 persons.  Addiction disorders disproportionately affect young adults, with opioid overdoses accounting forone in every five deaths of Americans between the ages of 25 and 34. This is the grim face of the epidemic today.

While the Attorney General and U.S. courts fight to determine the role pharmaceutical companies such as Purdue Pharma had in precipitating our nation’s drug crisis – as well as their prior knowledge of the addictiveness of drugs like OxyContin – patients, physicians and local communities continue to battle the epidemic on the front lines. From controversial measures like safe injection sites, to collection programs for unused pills as well as new medical policies designed to reduce overprescribing, communities across the country are developing and implementing innovative ways to address the epidemic.

One of the strategies outlined in recent months comes from the Centers for Medicare & Medicaid Services (CMS), which describes a three-pronged approach to fighting the epidemic: opioid use disorder (OUD) prevention, treatment and improved data utilization in electronic health records (EHRs). The cornerstone of this strategy – to equip health workers on the front lines with access to real-time data about patient prescribing patterns – is a key aspect of CMS’s roadmap that health technology leaders are still exploring today. And, while much of the necessary data is already being collected through various means, getting it in front of prescribers when and where they need it – and in a useable format – is another matter.

The full Forbes article can be viewed at this link.  

Primary Care Clinician Adherence to Specialist Advice in Electronic Consultation

Electronic consultation (eConsult) services can improve access to specialist advice. Little is known, however, about whether and how often primary care clinicians adhere to the advice they receive. We evaluated how primary care clinicians use recommendations conveyed by specialists via the Champlain BASE (Building Access to Specialists through eConsultation) eConsult service and how eConsult affects clinical management of patients in primary care.

This is a descriptive analysis based on a retrospective chart audit of 291 eConsults done between January 20, 2017 and August 31, 2017 at the Bruyère Family Health Team, located in Ottawa, Canada. Patients’ charts were reviewed until 6 months after specialist response for the following main outcomes: implementation of specialist advice by primary care clinicians, communication of the results to the patients, method, and time frame of communication.

Primary care clinicians adhered to specialist advice in 82% of cases. Adherence ranged from 62% to 93% across recommendation categories. Questions asked by primary care clinicians related to diagnosis (63%), management (27%), drug treatment (10%), and procedures (1%). Recommendations of the eConsult were communicated to patients in 79% of cases, most often by face-toface visit (38%), telephone call (32%), or use of the patient portal (9%). Communication occurred in a median of 5 days.

We found little evidence of barriers to implementing specialist advice with use of eConsult, which suggests recommendations given through service were actionable. With a high primary care clinician adherence to specialist recommendations and primary care clinician–to-patient communication, we conclude that eConsult delivers good-quality care and improves patient management.

The full article can be downloaded below.  

Visit Planning Using a Waiting Room Health IT Tool: The Aligning Patients and Providers Randomized Controlled Trial

Time during primary care visits is limited. We tested the hypothesis that a waiting room health information technology (IT) tool to help patients identify and voice their top visit priorities would lead to better visit interactions and improved quality of care.

We designed a waiting room tool, the Visit Planner, to guide adult patients through the process of identifying their top priorities for their visit and effectively expressing these priorities to their clinician. We tested this tool in a cluster-randomized controlled trial with usual care as the control. Eligible patients had at least 1 clinical care gap (eg, overdue for cancer screening, suboptimal chronic disease risk factor control, or medication nonadherence).

The study (conducted March 31, 2016 through December 31, 2017) included 750 English- or Spanish-speaking patients. Compared with usual care patients, intervention patients more often reported “definitely” preparing questions for their doctor (59.5% vs 45.1%, P <.001) and “definitely” expressing their top concerns at the beginning of the visit (91.3% vs 83.3%, P=.005). Patients in both arms reported high levels of satisfaction with their care (86.8% vs 89.9%, P=.20). With 6 months of follow-up, prevalence of clinical care gaps was reduced by a similar amount in each study arm.

A simple waiting room–based tool significantly improved visit communication. Patients using the Visit Planner were more prepared and more likely to begin the visit by communicating their top priorities. These changes did not, however, lead to further reduction in aggregate clinical care gaps beyond the improvements seen in the usual care arm.

The full article can be downloaded below.  

Implementation best practices: Getting healthcare analytics right

Data and analytics have become increasingly critical to the operation of any successful healthcare organization. And with the advent of healthcare imperatives such as value-based care and population health management, analytics technology has become more important than ever.

Here, four experts in healthcare analytics technology offer their advice and suggestions for healthcare CIOs implementing analytics in their provider organization. These are a variety of best practices for analytics implementation in healthcare.

Best Practices

• Look to stakeholders and required data - Implementing an analytics system first requires outcomes defined by multiple stakeholders that second drives alignment on what data elements are required, said Bradley Hunter, a research director at KLAS Research.
• A shared vision, and AI - In the past decade, new incentives and value-based programs that reward payers and providers for proactively managing the health of members have increased their collaboration and created an even greater need for data and analytics to get the right care to the right patient at the right time.  Start with applications of data and analytics that can show an immediate impact by freeing up time and cost.
• Analysis and collaboration - Conduct a stakeholder analysis of existing conditions so one can best understand how the change management will affect each of the stakeholders.  Furthermore, technology vendors and CIOs should work hand in glove with a clinical sponsor for all new initiatives.

The full Healthcare IT News article can be viewed at this link.  

Health Care Technology Predictions For 2019

In 2019, health care information technology (HIT) in the U.S. will continue to be transformed by external forces from around the world. To be honest, the whole of health care is feeling the pain of this evolution, and there are challenges that need to be met head-on.

But there are also inklings of light at the end of the tunnel. The digital transformation of this sector is only in the embryonic stages, but there’s clear evidence of enormous development and growth on the horizon. Here are my top five predictions for health care technology in 2019.

1. There Will Be A Major Push Toward Truly Digitized Health Care
2. AI Will Start To Penetrate The Broader Health Care IT Landscape
3. The Transition From Data Centers To The Cloud Will Accelerate
4. Cybersecurity Attacks Will Continue To Escalate
5. The Mobile-First Movement Will Gain More Traction

The full Forbes article can be viewed at this link.  

AI Will Not Replace Doctors, But It May Drastically Change Their Jobs

There’s strong consensus that AI won’t replace doctors. Arguing that it can goes not just against the complexity of what doctors actually do, but such a stance fails to realize the need for a human touch. You will want a human to hold your hand when discussing your cancer diagnosis. Empathy is critical in such life-changing moments. The level of human connection you’ll have with your doctor will directly influence how well you feel, how likely you are to stick with a treatment plan, and how you and your family will remember the trauma for decades to come.

But agreeing that the human doctor will always be there doesn’t reflect the massive changes and risks to their jobs. Doctors essentially do three things: diagnosis (what’s wrong with me?), treatment (what’s the plan?) and prognosis (how long before it gets better?). All three core tasks are being gradually performed by AI systems that employ machine learning, deep learning, natural language processing and time series forecasting.

The full Forbes article can be read at this link.