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 below- average 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.


Be prepared


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 from


28 US Captive . April 2011


“Creating a positive spiral requires analysing and investing in appropriate staffing. This generates healthy morale, which produces a more desirable risk environment.”


benchmarks 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.


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.


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