With families, patients and lawyers paying increasingly close attention to quality of care, PointRight outlines the significance of effective risk analytics to the assessments of US healthcare providers.
Executive vice president, PointRight Inc.
Business development, PointRight Inc.
A $114 million verdict in Florida for inadequate protection of a resident at risk of falling; a class-action lawsuit settled for $50 million in California for inadequate staffing; $100,000 dollars spent in legal fees overturning a survey citation. These are just a few examples of the unforeseen expenses that can devastate the game plan of predictable results and financial stability for any captive. While unexpected events seem to happen all of the time, the impact on the organisation’s cost of risk and the ability to attract patients that provide the most attractive revenue opportunity is significant. Realistically, many seemingly unexpected events can be anticipated and avoided using data analytics.
Attract revenue, manage risk
Today, the cost of risk is highly focused on the sum total of an organisation’s operations that relate to risk, including self-insured losses and related loss adjustment and administrative expenses. This perspective, however, is too narrow. Building a captive with members that enhance their revenue opportunity and minimise their risk is an achievable goal, and accordingly, captives that take a proactive stance and make use of available tools will reap financial rewards and attain expected results. Data analytics can help captives be proactive and nimble by identifying trends early, while recognising, measuring and monitoring areas of greatest exposure. For example, data analytics can do the following:
• Validate that publicly reported information is accurate
• Ensure patient care and conditions are coded correctly and completely
• Identify patients with conditions that lead to costly litigation
• Anticipate a facility’s next survey citation
• Answer the question: does this facility meet the risk profile for my captive?
Check information in the public domain
In healthcare organisations, reputation is directly and positively correlated with revenue. Healthcare reform will increase the amount of information available to the public and requirements for transparency will provide more insight into an organisation’s capital structure. As accountable care organisations (ACOs) are launched, reputation and results will drive referrals; facilities that don’t perform will lose revenue opportunity. Not surprisingly, prospective patients and their family members are reluctant to select a healthcare provider with belowaverage performance or a high number of complaints, making it critical to verify that this information is reported correctly. Furthermore, referral sources, such as physicians and hospital discharge planners, access this public information (along with word-of-mouth) for the purpose of making good placement choices for their rehabilitation patients.
Don’t leave dollars on the table
Accuracy and consistency are vital to data integrity of any kind. In long-term care, the minimum data set (MDS) record is used to capture patient health and is the basis for government reimbursement. Tools are available to check the coding and consistency, as well as run clinical and statistical tests on each MDS assessment to ensure data integrity and assessment validity. One such tool, the data integrity audit (DIA), checks for logical consistency, clinical consistency, relationships between symptoms and diseases, relationships between treatments and disabilities, and overall coding of the MDS. This kind of data analytic tool not only maximises the revenue opportunity, but ensures that data presented makes sense and will stand up to government scrutiny.
By using data analytics, you can predict and prepare; the tools pinpoint patients with high-risk conditions (such as high likelihood to fall, develop pressure ulcers, or die) so that appropriate care planning can take place and provide insight to assist in managing family expectations.
Also, of great concern, time and cost is the survey process. The initial cost to facilities is in management and staff time. If the survey does not go well, added costs may come from responding to citations, revising care processes, and covering consulting or legal expenses. The greater cost, and the more difficult to quantify, is to business lost or reputation damaged by deficiencies. Tools that enable a facility to benchmark its performance against others in its survey district or state, and anticipate the next likely citation, are available today.
Captive risk profile, match or miss?
PointRight studies professional liability loss costs for long-term care. In a recent study looking at data for 4,000 facilities from 2003-2008, PointRight found that 50 percent of expected loss could be predicted, and hence possibly prevented, and that the difference between the best and worst-performing facility in a state was 15-fold. By utilising a comprehensive database of public and private information such as occupancy, payer mix, staffing analysis, survey results, survey deficiencies, and measures of structure, care processes and clinical outcomes, data elements of known predictive value are combined with loss history to create a quantitative model for measuring risk. Potentially modifiable risk factors that deviate adversely frombenchmarks and have significant impact on risk are identified, and a risk management prescription is developed to focus on those factors. A facility’s performance can then be benchmarked against other facilities within the captive to determine in advance whether or not it meets the captive’s profile.
Risk and revenue spiral
While reducing risk is always important, over time, lost revenue equates to lower investment in quality improvement programmes, less money available to staff improvement and a corresponding decline in a facility’s defensibility. Therefore, a damaged reputation from survey deficiencies, resident complaints and poor-quality measures, whether valid or not, can have a negative impact on the cost of risk and trigger a downward spiral that can be difficult to stop. Consider staffing—as the largest line item in a long-term care facility’s budget, this is where the axe most often falls. Some facility administrators respond to diminishing revenues by adjusting the staffing matrix from RNs (registered nurses) to less expensive LPNs (licensed practical nurses) or reducing CNAs (certified nursing assistants). Over the long term, however, these shifts will not deliver the expected savings.
"Creating a positive spiral requires analysing and investing in appropriate staffing. This generates healthy morale, which produces a more desirable risk environment."
When facilities fail to properly staff to meet patients’ needs, risk increases. It just takes one claim or one citation to cancel out any expected savings from using a lower-cost staffing matrix. Inappropriate staffing also leads to turnover, which results in utilisation of contract workers and discontinuity of resident care. Each of these impacts quality of care and can result in more unanticipated costs and increased risk. Should a claim occur, the $100,000 paid to an attorney for the defence of the facility will impact cash flow, cause the facility to forgo other important expenditures and be money wasted with no added value. It actually perpetuates more risk.
Creating a positive spiral requires analysing and investing in appropriate staffing. This generates healthy morale, which ripples through the facility and produces a more desirable risk environment.Even in the best-staffed facilities, unexpected events can occur. The critical difference is that facilities that can support their staffing decisions with analysis and quantitative data are ultimately more defensible and pay less for their mistakes.
Linking risk analytics, risk management and loss control
Understanding the cost of risk isn’t limited to determining which facilities meet the captive’s desired risk profile. Rather, understanding total cost of risk is an ongoing predictive aspect of risk management and includes loss control. In a recent study based on a large self-insured long-term care captive, the impact of implementing just one dimension of data analytics, DIA, had a significant affect on the number of professional liability losses. First, the 100 facilities in the study were divided into two groups of 50: the top 50 best users of the tool and the 50 worst users of the tool. In the category of best users of the tool, 16 percent of the 50 facilities had experienced losses in the year before utilising DIA. In the year following DIA implementation, the occurrence of losses dropped to 10 percent. In the category of worst users of the tool, 32 percent of the facilities had losses in the year before DIA. In the year following DIA, that rate dropped to 26 percent. The actual number of losses across the board decreased from 121 to 101 after the implementation of DIA. For loss control, this captive can now analyse at the time of claim report if an analytic defence is available for the claim.
Data analytics: a source for answers
More and more, plaintiff attorneys, families and surveyors are relying on data and data analytics to identify who, what, where and when they should investigate. Using data analytics, surveyors scour and interpret reported information to predetermine deficiencies. Consequently, it’s helpful for captives and their members to avail themselves of these same tools to make preemptive strikes against risk.
With the right mix of data-based analytic tools, captives can expand their understanding of the cost of risk to incorporate indirect costs that have a significant impact on future claims and help drive revenue to the captive members. Ultimately, these same tools can drive the development of a targeted and measurable risk management prescription for each captive member and employ a data-based defence for loss control. The result is a financially strong captive. Investigate how data analytics can rapidly supply the answers you need to chart a successful path into the future.
Mary Chmielowiec is executive vice president at PointRight, Inc. She can be contacted at: email@example.com.
Brad Granger is business development executive at PointRight, Inc. He can be contacted at: Brad.Granger@pointright.com For more information, please visit www.pointright.com
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