No More Blame Game: How to Use Patient Outcomes Measurement to Boost Quality and Provider Performance
Fair or not, if your patients don’t do well, your physicians can be tagged as poorly performing providers.
But there are ways to change the dynamic for your organization by effectively using patient outcomes measurement to structure and drive a quality program that benefits both patients and providers.
Tracking the health and status of patients—“how patients do”—is the Holy Grail of quality measurement. Despite the fact that it is very difficult to identify a direct cause and effect between provider action and patient outcomes, quality programs are shifting the emphasis to patient outcomes and attributing performance to physicians. This is the new reality of value-based health care.
The reality familiar to every physician, however, is that a lot happens outside of the exam room or hospital that impacts patient health. Socioeconomic status, personal habits and social support heavily influence outcomes, but are mostly beyond the reach and responsibility of health care professionals. So, as you build your quality program, how do you break through some of the barriers to fair and accurate performance assessment?
What are Patient Outcomes and How Are They Measured?
The first step is to understand how outcomes are defined and measured, and some of the inherent limitations of the measurement process.
Here are some common patient outcomes that are turning up in various performance measures such as PQRS:
- Functional status
- Utilization (e.g. visits to ER)
- Intermediate outcomes (e.g. HgbA1C)
- Absence of complications
- Absence of progression of disease
- Patient satisfaction
- Symptoms (e.g. angina)
The outcome may be the result of a care episode, such as an emergency room visit or an operative procedure, or may reflect the patient’s general health status. Some of the outcomes listed here are notable for being the absence of complications or disease progression that might otherwise have occurred after an event when health was compromised (e.g. ER visit, disease complication, symptom).
Measuring outcomes is a challenging and evolving process. Symptom scores and laboratory values are the most easily measured because they use absolute values or variables; these will generally be found in EMRs. However, symptoms vary depending on who is asking, and how they are asking. Other outcomes are also tricky to measure. For example, utilization outcomes can be measured in terms of the time from one occurrence to the next, such as the number of days or months without an ER visit or hospitalization; or utilization can simply be defined as a ratio of number of visits per thousand patients. But the different methods have very different implications. Functional status and patient satisfaction necessitate input from the patient, but most current survey tools are insufficiently informative for effecting change.
Absence-related outcomes are also very problematic. Surgeons frequently do not code complications that occur post-discharge or post-procedure, and there is no easy way of identifying these without asking the patient, whose responses must then be validated. Information on both complications and progression of disease may also be limited by lack of aggregated data from multiple providers (e.g. radiology, primary care) that would help to create a full patient picture.
How to Use Outcomes to Better Measure Provider Performance
Given these limitations, how can you establish a quality program in which outcomes measures provide a better picture of your providers’ performance? Here are a number of key factors:
- The outcome must have the potential for being influenced by the provider through an intervention, either through direct action or in conjunction with the patient. Interventions might include calling in patients for educational visits, reviewing data with patients, requesting patient reporting of home-based results, or developing processes to avoid complications, such as DVTs or other common post-surgical problems.
- The providers must understand and accept the outcomes under measurement, and review the relevant data, first to understand and interact with the outcome results, and then to develop a process for improvement. This will be significantly enhanced if leadership institutes interventions through population health and applies these to discrete patient groups.
- Outcome measurement, alone, is not enough. Next step must be a search for the reason why the outcomes occurred and how to change them, if necessary. Looking for whom to blame or how to avoid blame is not constructive. The process of improvement must include a mechanism for physicians to add reasons and data to the inquiry.
- An interactive dashboard tool that enables physicians to review outcomes and provide responses is essential. The physician must be able to see all of the data, compare it with peers and other patients, and provide reasons or interventions.
- Interventions should be centrally tracked and monitored to see what is working, with what populations of patients. This is fundamental for a good population health program.
- Attribution of patients to physicians may be incorrect and should allow for adjustment. Physicians should be able to add feedback about their role—or lack of it—with respect to an individual patient.
Using outcomes in quality measurement creates an opportunity to get physicians more interested and involved in quality, if your process is structured as a win-win program. Providers are understandably edgy about outcome attribution that seems unfair or inaccurate. Here’s the key: Make the process one of outcomes inquiry leading to possible interventions and improvement, rather than a series of wrongdoing accusations with the expectation of “correction.”
Founded in 2002, ICLOPS has pioneered data registry solutions for improving population health. Our industry experts provide comprehensive PQRS Reporting with VBPM Consultation and Population Health with Grand Rounds, solutions that help you both report and improve your performance. ICLOPS is a CMS Qualified Clinical Data Registry.