Posts Tagged ‘patient care’

Infographic: Staying Ahead of Rising Costs of Quality Patient Care

October 25th, 2019 by Melanie Matthews

Health systems, healthcare providers and patients are all feeling the sting of skyrocketing healthcare costs, according to a new infographic by ShiftWise, Inc.

The infographic examines why costs are rising, how fast they are rising and how health systems can reduce expenses while retaining care quality.

Profiting from Population Health Revenue in an ACO: Framework for Medicare Shared Savings and MIPS SuccessA laser focus on population health interventions and processes can generate immediate revenue streams for fledgling accountable care organizations that support the hard work of creating a sustainable ACO business model. This population health priority has proven a lucrative strategy for Caravan Health, whose 23 ACO clients saved more than $26 million across approximately 250,000 covered lives in 2016 under the Medicare Shared Savings Program (MSSP).

Profiting from Population Health Revenue in an ACO: Framework for Medicare Shared Savings and MIPS Success examines Caravan Health’s population health-focused approach for ACOs and its potential for positioning ACOs for success under MSSP and MACRA’s Merit-based Incentive Payment System (MIPS).

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Guest Post: Artificial Intelligence’s Impact on the Future of Patient Care

June 11th, 2019 by Steve Bradshaw

Healthcare organizations that adopt AI will become more efficient; their professional judgments will become more accurate and their health predictions better informed.

In the near future, applications of artificial intelligence (AI) will play an increasingly important role in healthcare services. AI’s ability to assist in managing electronic health records, as well as in diagnosing and treating patients, will prove too valuable for healthcare providers and administrators to ignore. By adopting AI, their operations will become more efficient, their professional judgments more accurate, and their health predictions better informed.

Making Electronic Health Records Management More Flexible

Electronic health record (EHR) systems are expensive to maintain and cumbersome to use. AI is already being applied to make EHR systems more efficient. AI can extract and index information from provider notes and help personalize treatment plans. In the near future, AI could make it easier for providers to continually customize their EHR systems to better meet the changing needs of their practices to save time and improve patient outcomes.

Improving Diagnoses and Treatment

Computers can analyze massive amounts of data. They also excel at recognizing patterns. Put these two abilities together, and you get AI’s extraordinary power to successfully perform tasks that previously required human intelligence—in some cases, even surpassing humans in accuracy.

In a process called “deep learning,” scientists train AI systems using large amounts of labeled data. The AI is then able to identify patterns by itself when given data to which it hasn’t yet been exposed. In healthcare, deep learning will train AI systems to help clinicians provide more accurate diagnoses, identify patients at risk of various diseases and conditions, and create individualized treatment plans.

A recent study found that AI outperformed radiologists at finding cancer on CT scans used to screen smokers for lung cancer. When prior scans were not available, the AI did better than all six radiologists in the study, coming up with both fewer false positives and fewer false negatives. When there were prior images, the AI and the radiologists were equally accurate. Although this was a preliminary study, it shows how near-future applications of AI can provide clinicians with more accurate diagnostic and predictive information than is available to them now. The results of this study also may enable radiologists to make more frequent life-saving identifications of early-stage cancer and other diseases.

In addition to reading images, AI will be able to extract useful information from patients’ medical records. By finding patterns in the medical histories, AI could provide warnings when patients are at risk of developing conditions such as sepsis, diabetes or heart disease. An area of intense interest now is using AI to identify which patients are most at risk of being re-admitted to a hospital after being discharged.

AI may also reduce the amount of trial and error involved in prescribing medications and other treatments. It can help identify the treatments most likely to succeed based on each patient’s unique combination of genes, medical history and environmental influences.

The Time Is Right

In the past, there was more resistance to using AI in healthcare. Now, providers and the public are increasingly ready to accept the use of this cutting-edge technology to make healthcare administration more efficient and providers’ decisions more accurate.

Healthcare professionals are seeing what AI can bring to their practices. At the same time, the public has gotten used to the idea of self-monitoring their health using smartphones and smart watches. More work still needs to be done to implement industrywide standards and to safeguard patient privacy, but the benefits of AI in healthcare now appear overwhelming. It is inevitable that healthcare providers and organizations will soon come to increasingly rely on AI applications.

This could be just the beginning. How well AI can “think” depends in large part on how much computing power is available — and that power is increasing exponentially.

Healthcare in the more distant future may include AI applications that we can’t even imagine now. In the meantime, healthcare providers and administrators may soon enjoy greater efficiency and cost containments, while patients could benefit from more accurate diagnoses and effective treatments.

Sources

https://www.nytimes.com/2019/05/20/health/cancer-artificial-intelligence-ct-scans.html
https://www.nature.com/articles/s41591-019-0447-x
https://hbr.org/2018/12/using-ai-to-improve-electronic-health-records
https://becominghuman.ai/the-role-of-ai-in-healthcare-technology-6c33a6eee18c
https://www.internationalsos.com/client-magazines/in-this-issue-3/how-ai-is-transforming-the-future-of-healthcare
https://www.appian.com/blog/the-growing-role-of-ai-in-healthcare/

About the Author: Steve Bradshaw began working in the medical gas and environmental industry in 1991, starting Evergreen Medical Services, Inc. in the Carolinas in 1997.

Infographic: The Quality of Nursing, Patient Care

April 16th, 2014 by Jackie Lyons

Seventy-five percent of Americans 30 years and older are more concerned with the quality of nursing staff in hospitals than with the availability or accessibility of electronic medical records (EMRs), according to a new infographic form API Healthcare.

While confident in nursing abilities, a majority of consumers feel nurses are spread too thin, which is impacting the quality of patient care. This infographic also provides data on the quality of nursing care, impacts of the Affordable Care Act (ACA), consumer concerns and quality of patient care.

Looking for other ways to increase patient satisfaction? You may also be interested in The Patient-Centered Payoff: Driving Practice Growth Through Image, Culture, and Patient Experience, which is filled with easy-to-implement ideas. This 260-page resource describes how the patient-centered movement has changed medical practice and offer insights into the opportunities this new environment provides to practices.

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5 Barriers to Optimal Care in the Post-Acute Setting

January 22nd, 2014 by Jessica Fornarotto

Summa Health System’s care coordination network of skilled nursing facilities (SNFs) is working to decrease fragmentation, length of stay and unnecessary readmissions while improving outcomes of care. Mike Demagall, administrator of Bath Manor & Windsong Care Center, a participant in this network, identified five barriers to patient care that originated in the acute care setting.

First, we found a lack of quality information received upon transfer from an acute care to a nursing facility and the lag time in identification of post-acute bed availability. The social worker was calling or faxing information to a facility, and the facility took up to 24 hours to respond as to whether a bed was available. That person may have been ready that day; instead it postponed that discharge another day.

We also had barriers to the patient’s acceptance of the need for post-acute care. Social workers and care coordinators at the bedside tell them when it is time for rehabilitation.

The next barrier was family expectations. Does the family feel that they need to go to the nursing home? The hospital staff and the insurers had to spot the appropriate levels of care. One of the concerns we had was, ‘Is this going to send a lot of our patients — our referrals — to home healthcare and decrease our referrals by participating in this?’ That happened to not be the case at all.

There was still a lack of knowledge and respect toward long-term care (LTC). All the discharge planning individuals, which were the case manager nurses and social workers, were able to tour the facility. Each facility had the opportunity to present their services and what they do. That helped with the overall cohesion of the group, and it moved this project forward.

There was also a lack of quality information received from the nursing facilities on the transfer to an emergency department (ED). That was information that we needed to get back, just as we were asking for information as those residents were coming in.

Excerpted from: 7 Patient-Centered Strategies to Generate Value-Based Reimbursement

HINfographic on Care Transitions: Coordinating a Smooth Move Between Care Sites

July 1st, 2013 by Jackie Lyons

Proper management of transitions in care — the handover of an individual’s care from one health setting to another — has the potential to dramatically hasten that person’s return to health, as well as reduce the likelihood of a return ER visit or rehospitalization.

Transitions of care are a checkpoint not only to engage patients and caregivers in proper post-care but also to confirm providers have a complete picture of patients’ health so that handovers are seamless.

This HINfographic on care transitions illustrates the proper handling of care transitions, including transition trouble spots, red flags for care management, favored models of care, coordinators of care transitions, transition program components and barriers, and what’s working in current programs.

care transitions infographic

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You may also be interested in this related resource: 2013 Healthcare Benchmarks: Care Transitions Management.