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Physician burnout has been linked to an increase in medical errors, lower quality of care, and reduced work satisfaction. This week's news roundup focuses on physician burnout, the top burdens facing physicians today, interventions that are helping, and how the digitization of healthcare has exacerbated the problem.
For healthcare organizations, the ability to analyze problems and implement timely, effective improvements is necessary to maintain a competitive advantage, requiring a consistent, systematic approach to introduce and implement change. By developing a new strategy focused on uniform adoption, education, and ongoing oversight, Community Health Network changed the way it approached all organizational improvement efforts.
In today’s challenging environment, healthcare leaders must seek opportunities to boost revenue through improved financial performance and reimbursement. Some common strategies include reducing the number of outstanding bill hold accounts, reducing A/R days, and managing discharged not final billed (DNFB) cases. This article tackles, the following topics:
So far, the EHR hasn’t delivered on its original intent to improve patient care with more efficiency and personalization and lower cost. Instead, physician users blame the systems for worsening their experience and the quality of their care in significant ways:
Employer-provided health insurance continues to be a hot topic-and a problem-for both providers and consumers. This week's news roundup examines the issue, including why employers provide health insurance in the first place, why Europeans don't get huge medical bills, how some employers are choosing their employees' doctors, and how data will help shape the future of employer insurance.
Employers are always looking for ways to reduce one of their biggest expenditures–the cost of providing health insurance to employees. Many employers have explored solutions such as adding wellness plans, reducing usage, and providing different provider access mechanisms, all with modest success. Stemming the rising costs of health insurance requires management to understand and improve healthcare outcomes for their employee and dependent populations. Changing the future of employer health insurance will require a multi-faceted approach:
With patients responsible for an increasing amount of their healthcare costs, self-pay accounts are now the top contributor to bad debt for hospitals and health systems—accounting for more than $55 billion annually. Allina Health partnered with Health Catalyst, using catalyst.ai™, to create a predictive model that could successfully support a propensity to pay strategy.
A hot topic in healthcare right now, especially in the medical coding world is the Hierarchical Condition Category (HCC) risk adjustment model and how accurate coding affects healthcare organizations’ reimbursement. With almost one third of Medicare beneficiaries enrolled in Medicare Advantage plans, it’s more important than ever for healthcare organizations to pay attention to this model and make sure physicians are coding diagnoses appropriately to ensure fair compensation. This article walks through basics of the risk adjustment model, why coding accuracy is so important, and five action items for interdisciplinary work groups to take. They include:
This week's news roundup is all about data and the life science industry: why extended real-world data is the industry's number one asset, why pharma R&D needs to adopt a data science mindset, how the cloud can transform pharma, and, on the flip side, why the industry is resistant to embrace cloud technology. Lastly, the Novartis CEO who wanted to bring tech into pharma now explains why it's so hard.
When health system clinicians make care decisions based on their organization’s EHR data alone, they’re only using a small portion of patient health information. Additional data sources—such as health information exchanges (HIEs) and patient-generated and -reported data—round out the full picture of an individual’s health and healthcare needs. This comprehensive insight enables critical, and sometimes life-saving, treatment and health management choices. To leverage the data from beyond the four walls of a health system and combine it with clinical, financial, and operational EHR data, organizations need an interoperable platform approach to health data. The Health Catalyst® Data Operating System (DOS™), for example, combines, manages, and leverages disparate forms of health data for a complete view of the patient and more accurate insights into the best care decisions.
While healthcare data is an ever-growing resource, thanks to broader EHR adoption and new sources (e.g., patient-generated data), many health systems aren’t currently leveraging this information cache to its full potential. Analysts can’t extract and analyze a significant portion of healthcare data (e.g., follow-up appointments, vitals, charges, orders, encounters, and symptoms) because it’s in an unstructured, or text, form, which is bigger and more complex than structured data. Natural language processing (NLP) taps into the potential of unstructured data by using artificial intelligence (AI) to extract and analyze meaningful insights from the estimated 80 percent of health data that exists in text form. Though still an evolving capability, NLP is showing promise in helping organizations get more from their data.
Be prepared to have fun in this interactive, “choose your own adventure” style experience, where you’ll discover how investing in a deliberate, principle-based strategy can help you navigate the complexities of data governance and maximize the value of data for outcomes improvement. Join the webinar and learn:
How are 2019 Predictions Holding Up? As the first quarter comes to a close, we’re taking a look how predictions for 2019 are holding up so far. This week, our news roundup examines population health trends to watch, healthcare predictions for 2019 to question, hospital revenue cycle trends, and how trends in appointment-based-businesses will affect healthcare this year. Population Health Trends to Watch, Trends to Question in 2019 healthcare organizations cannot afford to ignore consumers in 2019, as a number of major trends shape the …
Opportunity analysis uses data to identify potential improvement initiatives and quantifies the value of these initiatives—both in terms of patient care benefits and financial impact. This process is an effective way to find unwarranted and costly clinical variation and, in turn, develop strategies to reduce it, improving outcomes and saving costs along the way. Standardizing the opportunity analysis process makes it repeatable and prioritizes actionable opportunities. Quarterly opportunity analysis should follow four steps:
The life science industry has historically relied on sanitized clinical trials and commoditized data sources (largely claims) to inform its drug development process—an under-substantiated approach that didn’t reflect how a new drug would affect broader patient populations. In an effort to gain more accurate insight into the patient experience and bring drugs to market more efficiently and safely, the industry is now expanding into extended real-world data (RWD). To access the needed breadth and depth of patient-centric data, life science companies must partner with a healthcare transformation company that has three key qualities:
The life science industry has historically relied on sanitized clinical trials and commoditized data sources (largely claims) to inform its drug development process—an under-substantiated approach that didn’t reflect how a new drug would affect broader patient populations. In an effort to gain more accurate insight into the patient experience and bring drugs to market more efficiently and safely, the industry is now expanding into extended real-world data (RWD). To access the needed breadth and depth of patient-centric data, life science companies must partner with a healthcare transformation company that has three key qualities:
Alongside widespread efforts to improve healthcare quality, safety, and interoperability, the demand for electronic health information exchanges (HIEs) is increasing. This week’s news roundup features news about HIEs, including the case for combining HIE data with an analytics platform, how HIEs can enable public health reporting when EHRs fall short, how they can help remedy long emergency stays, why mental health providers oppose behavioral health EHR requirements, and the great conundrum of data liquidity in healthcare.
Data-driven decisions and analytics are critical for organizations and physician practices attempting to thrive under value-based care. With the help of data analytics, UTMB Health was able to focus on improvement efforts for specific patient populations and boost reimbursement based on DSRIP performance.
Bobbi Brown, MBA, and Stephen Grossbart, PhD have analyzed the biggest changes in the healthcare industry and 2018 and forecasted the trends to watch for in 2019. This report, based on their January 2019, covers the biggest 2019 healthcare trends, including the following:
