By Wonil Gregg, vice president of customer engagement and experience, DCPerform.
Whether you’re a customer or a worker, chances are you’re all too familiar with the persistent challenges of stockouts and overstocks across the healthcare industry. Stockouts can lead to missed opportunities or incomplete treatments, while overstocks cause unnecessary financial waste. The cost of unused drug waste in the healthcare industry costs $2.8 billion of medication per year.
Managing inventory in the healthcare industry requires striking the right balance between supply and demand and using great supply chain services. Fulfilling customers’ demands must balance maintaining an adequate yet cost-effective supply of goods and materials. Learn more about minimizing stockouts and overstocks to improve patient care and increase savings.
Mastering Forecasting and Inventory Analysis
Forecasting and inventory analysis have become essential tools for ensuring optimal stock levels in the ever-changing healthcare industry. Inventory forecasting uses data to drive decision-making. This is the application of information and logic to ensure you have enough products to meet customer demand without overstocking.
Analyze past trends and consumer behavior to accurately predict future demand
Consider complexities such as seasonality and trend forecasting
Ask questions to identify demand patterns, such as growth and spikes during specific seasons
Take into account planned marketing campaigns and other events that may impact sales
Utilize inventory management software for sophisticated demand forecasting
Prevent stockouts and backorders by optimizing inventory levels
Maximize profits by reducing excess inventory and minimizing storage costs
Continuously monitor and adjust inventory levels based on real-time data and insights
Constantly improve forecasting and inventory analysis processes for better accuracy and effectiveness.
Whether it is a small or large corporation, paying attention to these crucial metrics is key to staying competitive in today’s fast-paced market.
Harris Data Integrity Solutions, the leading provider of best-in-class patient data integrity services and software, has released a white paper that undertakes an in-depth examination of the healthcare industry’s chronic people matching problem. In addition to dissecting the challenges and impacts patient misidentification has on care safety, outcomes, and costs, People Matching in Healthcare: Challenges, Impact and Solutions explores efforts underway on multiple levels to identify a system-wide resolution to the problem.
Lora Hefton
“The tumultuous state of patient matching exposes patients to duplicative and unnecessary testing and services and care delays, exacerbates fraud risks, impacts public health emergency response, and costs the U.S. healthcare system over $6 billion annually in denied claims,” said Lora Hefton, executive vice president of Harris Data Integrity Solutions. “But the future is not as grim as the present might indicate, as our research also found that efforts to identify the right path forward are finding a foothold as stakeholders from across the healthcare continuum come together to remove obstacles and implement effective solutions.”
In People Matching in Healthcare: Challenges, Impact and Solutions, Harris Data Integrity Solutions’ patient identity experts highlight the efforts of Patient ID Now to eliminate legislative barriers hindering exploration of a unique patient identifier, and the collaborative’s work to establish the framework of a national strategy for effective patient identification and matching. They also look at the work undertaken by the Project US@ collaboration, spearheaded by the Office for the National Coordinator (ONC), that resulted in a technical specification for collection of patient addresses, and AHIMA for its related companion guide with operational guidance and best practices.
Hospitals routinely collect vast amounts of data, including information about patients’ health, care delivery, and organizational performance. This data could theoretically be utilized to drive huge improvements in health outcomes and operational efficiency.
Rather than this massive amount of health data being an advantage, it’s most often considered a burden as there are inconsistencies in documentation, aggregation methods, organization of, display of, and most importantly, how it’s used. There’s also a lack of resources required to effectively manage this overwhelming amount of information. The data gap not only leads to lost opportunities to improve healthcare but is a major contributor to some of healthcare’s current biggest issues like burnout and staffing. Hospitals are always striving to better leverage healthcare data. Revised processes that reduce manual inputs, eliminate redundancy, and include central EHR systems are a few goals that come to mind. However, some of the biggest wins will only be gained once we tap into more advanced tools that leverage artificial intelligence (AI). With so much medical information already available, including large complex data sets, sophisticated AI systems are just what the doctor ordered to get these data sets organized and in use. To unlock data, hospitals must incorporate more data science and use artificial intelligence (AI) methods to operationalize their learnings. Data science is an umbrella term for statistical techniques, design techniques, and development methods. It involves pre-processing analysis, prediction, and visualization, whereas AI is the implementation of a predictive model to foresee events. Advanced data science and AI can not only help organize all of this information, but also generate trends and insights so that hospitals can deliver more precise care, identify operational hazards, and create a more optimized approach for managing their current workload.
Many Sources of Information
The problem, as it stands, is too much information from disparate sources and in different formats. Hospital data comes from a variety of places, such as electronic health records, administrative systems, insurance providers, patient-submitted forms, local HR systems, hospital medical devices, and, remote monitoring services.
This information also comes in various forms, including structured digital data, physical documents, photographs, charts, and more. The volume and diversity of data make it difficult to store in conventional databases and format it for use across multiple frameworks.
Despite major changes in the healthcare system over the last few years, it’s still hard for many patients to get answers for the causes of chronic or sudden-onset health issues. The pandemic made things even worse by increasing testing delays and doctor visit wait times. Many private health care practices use commercial, off-site laboratories to provide test results to their patients. Some of these labs have improved the slow test result turnaround times that were exacerbated by the pandemic, and also now offer more tests to wider groups of patients.
Unfortunately, it can still take days if not weeks for many labs to return accurate results. At least 10 percent of patients say the most frustrating aspect of their medical experience is a long waiting period for results. An even larger percentage might have to wait weeks to get a visit to their personal care provider, only to be sent to a specialist provider and then on to a lab to get the specific test they need, and then wait even longer to get results back. Not to mention, these tests are frequently expensive and often subject to the whims of insurance.
However, through new developments with telemedicine, biometric technology, precision diagnostics, and diagnostics-as-a-service testing models, private medical practices gain advantage solving testing challenges and can offer faster care for patients who need a diagnosis now rather than in a few days or weeks. Here’s how private practices can best leverage new personalized health diagnostics technologies, protocols, and providers to improve individual care and give patients more control over their own health, both now and in the future.
By Eric Hyman, vice president of corporate and product marketing, GTT.
Telehealth and telemedicine have made rapid advancements in the past few years. However, while these advancements greatly improved access to healthcare services, they’ve also created a new avenue of attack for cybercriminals looking for valuable personal data or just to cause chaos.
A report by Omdia found that there has been an increase in cyberattacks on enterprises since 2020 across network applications, public and private clouds as well as fixed and mobile endpoints. The healthcare sector is experiencing the same too; healthcare organizations in the U.S. faced record-high cyberattacks impacting over 45 million patients last year.
One crucial solution to protect healthcare organizations against cyberattacks is Secure Access Service Edge (SASE), a framework first coined in 2019 that promises a better and more secure integration of software-defined networking and cloud-based security. The SASE framework provides advanced visibility, flexible connectivity, network reliability, application-aware routing, enterprise-grade security, and advanced protection for today’s rapidly expanding and evolving healthcare networks. It’s critical that forward-thinking healthcare security leaders understand what makes SASE such a vital tool to curb modern cyber threats and how to ensure proper deployments that help to keep their organization and its patients safe.
Why SASE?
In 2020, many healthcare companies were forced to explore telehealth and telemedicine options. This meant that IT and security teams suddenly had to securely connect doctors and nurses while they provided services online, and everyone had to move applications for managing sensitive health data to the cloud. This created a need for sophisticated security measures to keep patients’ records safe and ensure patient care wouldn’t be interrupted. This is when healthcare IT began to understand the SASE framework as an indispensable part of any post-pandemic cybersecurity strategy.
SASE integrates powerful network capabilities including software-defined wide area networks (SD-WAN) with a robust collection of security tools such as firewall-as-a-service , secure web gateway , zero-trust network access , and cloud access security broker. It supports organizations in setting and automating network and security policy, including secure, individualized, accelerated access to the cloud resources – especially critical for the healthcare sector. Each of these tools have evolving feature roadmaps that continue to address ever-changing threat actor behaviors and the changing needs of healthcare companies and their mission-critical applications.
Wasteful administrative costs are crippling healthcare. That’s the key finding of a recent research brief published by Health Affairs, a leading journal of health policy under the aegis of Project HOPE, a nonprofit international health education organization.
Claiming that nearly 50% of administrative spending is wasteful, the brief reveals that systemic non-standardization of procedures and widespread administrative billing errors as the major root causes for the waste.
While the report admits no single intervention is likely to make a dent in the problem – and its solution includes a multi-billion dollar, three-tier healthcare reform plan – there are ways modern healthcare practices can start reducing harmful administrative waste without having to reinvent America’s entire healthcare system.
The solution to address wasteful expenditures for individual clinics and practices can come through updating their current administrative procedures. Thanks to advances in AI and automation, this “modernization” can be accomplished relatively inexpensively and doing so has proven beneficial for both practice staff and their patients. Best of all, it’s a step the industry has already begun taking during the pandemic – instituting new protocols such as telehealth and pre-arrival appointment check-in. Seeing the process through is still not a high priority for a lot of practices who still ask themselves, where’s the tangible ROI on such an investment?
The pandemic showed us what a log-jam the traditional waiting room represents to the business. It showed us how much time front office staff spends on the phone, and in person, recording patient information and managing the practice’s work flow.
When waiting rooms were no longer a healthy option, it didn’t take long for solutions to become available that would effectively take the chore of waiting room “paperwork” requisition online. For many practices, it was a long overdue improvement.
Michigan Avenue Primary Care of Chicago knew they needed to consolidate disparate registration and appointment management systems into one integrated platform. At the same time, they needed to implement telehealth to accommodate their immediate care, primary care, and ENT practices. By adopting pre-arrival focused and fully customizable patient-intake solution, they were able to bring these services to their offices and successfully pivot during the pandemic lockdowns.
By Bobby Sherwood, vice president of product development, GuidingCare.
A lack of interoperability permeates U.S healthcare. Despite the rapid adoption of new technologies, we have failed to fully realize some of the most impactful opportunities they present. Data silos that hinder collaboration, efficiency, and innovation stubbornly persist across the industry. For health plans, embracing digital transformation to digitize process and improve member experience pays dividends, but can come with difficult integration and interoperability challenges if not done properly.
There has been a recent spotlight on government initiatives and regulations to address these growing concerns. Take the new CMS proposed rule on interoperability and prior authorization, which will require payers to implement an electronic prior authorization process, shorten the time frames for payers to respond to prior authorization requests, and establish policies to make the prior authorization process more efficient and transparent.
In a world where nearly anything can be instantaneously ordered from your mobile phone or laptop and delivered overnight, it seems inconceivable that prior authorizations – something so critical to member and population health – is managed by an antiquated system. This seamless exchange of data will reduce provider abrasion, improve the member experience and potentially their health outcomes, and ultimately decrease the cost of care, as the manual effort and time linked to prior authorizations markedly decreases.
As we execute on the year ahead, interoperability remains top-of-mind for stakeholders: a new report suggests that barriers such as poor data quality and information sharing remain challenging to over 60% of healthcare executives. For health plans prioritizing interoperability, consider these three areas of focus:
By Richard Dion, PharmD, pharmacy clinical program manager for clinical surveillance and compliance, Wolters Kluwer Health.
In recent years, the data collected by health systems has skyrocketed in volume. Unfortunately, studies show that up to 97% of data collected in hospitals is not used to inform or improve care — an issue that could offer new opportunities for both providers and patients. Hot-button topics like inpatient Opioid Stewardship could benefit from an increased utilization of available data.
Institutions looking to leverage existing data to improve quality and safety of opioid use should consider several steps to create meaningful and attainable data-backed goals.
From the outset, it’s important to consider who would drive these programs within hospitals and health systems. Leadership roles, as well as day-to-day drivers of activities, will require thoughtful selection and designation. Leadership plays a critical role in overall organizational buy-in, while pharmacists within a health system can provide the education and support necessary for physicians to optimize electronic healthcare records (EHR) and other data to provide appropriate pain management options. With the recent relaxation of opioid prescribing guidelines from the Centers for Disease Control and Prevention (CDC) to no longer promoting strict thresholds for pain medication doses and duration, developing standardized opioid stewardship programs based on local data is critical.
When it comes to analyzing existing information for care decisions, utilizing local data is vital to a complete understanding of opioid use and patient needs within the health system. Some EHRs and third-party applications may have metrics and dashboards available, but sites may need to curate their own data to fit organizational needs. Technologies such as dashboards that offer a composite view of patient and prescribing data are invaluable to providers to identify patterns and at-risk patients. There may still be several areas where manual processes are prevalent and / or necessary. While individualized care for patients is important to maintain, creating structure using automation that can help identify patterns and insights from data can be invaluable in preventing and treating opioid use disorder (OUD) efficiently and effectively.
