Data, Information, and the Planning Process

In the last column, I talked about planning as an iterative process that should rely on a broad range of data from various technology resources. We’ll build on that idea today. Effective planning requires an inventory of the data available, its reliability, and its utility in creating actionable plans and then measuring the impact of those plans to create desired outcomes. As more payers move to value-based contracting, human services organizations have to be sure that their plans and their data align with the outcomes being sought by an organization’s key payers. In behavioral health, the growth of Certified Community Behavioral Health Clinics (CCBHCs) also focuses attention on outcomes and process measurement to insure that the organization delivers effective care in an efficient manner. And, finally, the changes in human resource management brought about by the pandemic mean that organizations are paying increasing attention to staff needs (salary, work-life balance, development opportunities, etc.). An effective strategic plan can balance the need to achieve targeted outcomes with the allocation of resources, particularly an organization’s most valuable asset – its staff. 

Measures of Effectiveness & Efficiency

Effectiveness measures are those that are outward facing – satisfaction with services, improvement in functioning, housing, achievement, reduction in symptoms, etc. Efficiency measures are inward facing – access to services, cost of services, readmission rates, lifetime utilization, financial performance, etc. Both are important and both need to be considered when establishing a new plan or evaluating progress. For human services organizations, efficiency measures are easier to establish than measures of effectiveness. Behavioral health has struggled to find measures that truly reflect treatment efficacy and most measures are proxies (community tenure, treatment adherence, ability to work, volunteer, study, etc.) or rely on scores on survey measures (usually self-report or based on therapist interpretation of that self-report) of symptomatology or functioning.

Efficiency measures are much clearer: How long does it take to receive services from first contact to first services (screening, intake, or actual service/treatment contact)? What is the rate of failed (“no show”) appointments? What is the average length of service delivery for each consumer subgroup? How much does each service cost to provide? What is the revenue per service? What is our average revenue cycle? What is the optimal productivity of staff? Each of these questions can be answered thoroughly by integrating data from several sources.

Examples of Efficiency Measures

Access to care can only be well understood if there is data about referral, scheduling, and services. It also requires data about staffing capacity and potential service volumes, which then requires integrating HR data with service data. This in turn is also impacted by the rate at which appointments are kept. No shows, cancellations, and reschedules cause lost service delivery time (and revenue) and inflate the cost per service (if cost per service equals the cost of the employees delivering those services and their overhead divided by the total number of services, then shrinking the number of services raises the cost). And it reduces the ability of other consumers to be seen.

How long clients receive services also affects capacity and cost per client. It is important to benchmark this against existing practice standards, and also requires information about demographics that can affect a consumer’s needs. Social determinants, for example, are known to impact lengths of stay, or readmissions. All of which also impact capacity and cost of services.

Cost per service requires knowing the service volume for a particular activity, and the amount of staff time used in that activity (including time spent in administrative functions that precede or follow service delivery), and the cost of the employees doing the activity (including their overhead). This information is critical to knowing whether the reimbursement you get is sufficient to cover the cost. This question also relates to making sure that the required volume of services required of staff is realistic and considers time off, the impact of vacancies, and other potential factors.

The revenue cycle is critical in managing cash flow. It requires integration of general ledger and service data with billing and collection data by payer to get a robust picture of process inefficiencies (or problematic payer relationships) that need attention.

And these are not all the possible questions. A robust plan will begin by asking the questions that are most critical to understanding the outcomes to be created and the processes that are critical to those outcomes, and thus must be adhered to and be efficient. The questions used here are generic – your plan needs to ask the right questions for your organization. Data can only lead to useful information and effective planning if it is able to answer the most critical and appropriate questions for your organization.

About the Author

Maggie Labarta

Maggie Labarta is Founder and Consultant at Impact Non-profit Consulting, having previously retired as CEO of Meridian Behavioral Healthcare. Labarta holds a Ph.D. in Clinical and Community Psychology and has extensive experience in both administration and clinical practice. She also has particular expertise in strategic planning, data and analytics as management tools, and organizational development. She provides consultative services for numerous community organizations.

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