Creating Valid Profiles of Physician Hospital Practices

Comparing the practice patterns of physicians can be challenging at the provider level. The simplest way to profile physicians' hospital practices is to rank them by their patients' length of stay and hospital charges. The assumption is that those physicians whose patients have a higher length of stay and/or charges are the physicians that have the high complication rates (e.g., wound infections, etc.), provide less than adequate patient care, (e.g., inappropriate antibiotic therapy leading to slower recovery), or are not practicing cost-effective care (e.g., inadequate planning or performance). The major problem encountered when judging physicians’ average length of stay or patient charges is that these data fail to take into account patient severity of illness. Some physicians may very well care for sicker patients as compared to other physicians and thus have appropriately higher lengths of stay and charges.

The underlying assumption of any method used to adjust for patient severity of illness is that resource use results from a complex mix of factors. In order to control for patient severity of illness risk adjustors must be applied to the data. The difficulty is choosing the risk factors to use. A risk adjustor that predicts one outcome (e.g., extended hospital stay) may not predict another outcome (e.g., use of high cost resources). Many diverse patient attributes affect risks, including age, sex, acute physiological stability, reason for hospitalization and severity of the condition, the extent of co-morbid illnesses, functional status, psychosocial and cultural factors, socioeconomic characteristics, and patient preferences. .

Is Your Data Severity Adjusted?

There are a large number of methodologies for adjusting measures on physician profiles according to the severity of their patients' illness. Many hospitals use discharge abstract-based severity measures such as 3M’s All Patient Refined DRGs (APR-DRGs). These systems rely only on data found in the discharge database to risk adjust patients’ severity of illness. The amount of information in this database is limited (e.g., diagnoses and procedures coded using ICD-9-CM; admission source; and discharge disposition). However, despite limited clinical information, discharge data offers the advantages of uniformity, availability, and computer readability. Some methods for risk adjusting patient populations use clinical data abstracted from patient records. These systems may be more clinically credible, however the cost of gathering additional information from patient records can be an impediment. Whether the additional cost is worth the effort continues to be hotly debated.

Quality managers should know whether or not the physician profile measurement data used to examine utilization patterns are risk adjusted. If physician profile data are not risk adjusted it may be impossible to draw strong inferences about inappropriate utilization practices based solely on length of stay and charge data. If the data are risk adjusted, quality managers should be aware of the factors that are used to arrive at the patient severity scores and what limitations may exist. For example, many severity measures do not include all patient characteristics that increase risk, such as physical functional status, patients' preferences for care and outcomes, cultural factors, and socioeconomic characteristics.

Risk Adjustment Not Always Necessary

Not all assessments of health care quality and cost-effectiveness need to include a severity of illness measure. For instance, data showing physicians’ rate of compliance with clinical practice guidelines recommendations does not need to be risk adjusted. Listed below are examples of measures that evaluate practice-related issues:

* Percent of patients with myocardial infarction for whom aspirin is ordered or the rationale for non-use is documented by the physician.

* Percent of patients with congestive heart failure for whom ACE (angiotensin-converting enzyme) inhibitor is ordered or the rationale for non-use is documented.

* Percent of patients undergoing total hip replacement who receive prophylactic antibiotics within the 1-hour window prior to surgery or the rationale for non-use is documented.

There is convincing evidence that both quality and cost-effectiveness suffers when recommendations found in evidence-based guidelines are not followed. The validity of these process measures does not depend upon differences in patients' severity of illness.

Monitoring of possibly avoidable hospital days also does not require a severity of illness measurement system. A possibly avoidable day is independent of the patient's severity of illness, and is determined instead on the patient's medical stability. Even very ill patients can be adequately managed at non-hospital, lower levels of care if they are medically stable. For example, each of the following patients could most likely be safely cared for at a lower level of care such as a skilled or subacute facility or at home with home care agency visits:

1) The patient who requires total nursing care following an uncomplicated completed cerebrovascular accident.

2) The uncomplicated patient who is post-hip replacement and only requires intensive physical therapy.

3) The medically stable patient with a liver abscess who requires chronic intravenous antibiotic therapy.

The data about possibly avoidable hospital days could show important differences in physicians’ practice patterns. Adjusting the data for patient risk factors is not necessary.

For some quality and cost measures, risk adjusted data can be an important adjunct. However, there are many performance measures that can be used on the hospital’s physician profiles that are not affected by patients' severity of illness.

To Learn More: Patrice L. Spath is available for in-house presentations on this and other health care performance improvement topics. For further details, visit Brown-Spath & Associates on the web at: http://www.brownspath.com or write to: Brown-Spath & Associates, PO Box 721, Forest Grove, OR 97116.

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