By Debra Wood, RN, contributor
October 4, 2013 - Despite healthcare providers’ push in recent years to improve patient satisfaction scores, these scores may not be the best way to evaluate care and good clinical outcomes, according to a new study from Thomas Jefferson University in Philadelphia. The research team refined the PRIDIT statistical methodology, originally used in fraud detection, to determine hospital quality.
“I foresee PRIDIT being a way for insurers to organize and understand all of the data,” said lead author Robert D. Lieberthal, PhD, assistant professor in the Jefferson School of Population Health. “In contrast, clinicians may want to draw down on a certain measure.”
While factors such as unit noise or the responsiveness of a nurse are critically important to patients, these same factors are more likely to characterize a large, busy urban hospital--busy because of high caseloads. And numerous studies have linked high caseloads to better medical outcomes, Lieberthal confirmed.
The Society of Actuaries commissioned the study to develop a way of predicting quality of hospitals, so insurance companies could plan reimbursement rates over years. It was published in Risk Management and Insurance Review.
Mike Nowak, spokesman for the society, explained that its members analyze health care data to better assess risks and quality. The society sponsors research to increase its understanding of different methodologies. At this point, the information is theoretical and may be used for pricing in the future, he said. He was not aware of any actuaries currently using PRIDIT to evaluate hospital quality.
Medicare and other insurers are moving toward paying for performance and better outcomes.
“We should find the measures that best reflect high-quality care as measured by clinical outcomes and reward hospitals and nurses for that,” Lieberthal said.
The PRIDIT statistical method, Lieberthal explained, is useful to sort through variables in different types of data. The authors did not determine which measures were most important. The data was risk-adjusted.
Liberthal and colleague Dominique M. Comer drew on hospital quality data from the Centers for Medicare & Medicaid Services’ Hospital Compare database and the patient satisfaction measures obtained from the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS). Additionally, they included American Hospital Association demographic data, showing hospital characteristics including teaching status and ownership.
The PRIDIT method is weighted heavily by factors including patient mortality rates and the number of beds at the hospital, with the idea that more beds indicates more cases and better outcomes. The method allows for comparisons of different hospitals using the same metrics.
Lieberthal found that large busy hospitals with high volumes get the best outcomes, year after year. However, those hospitals might not score well on metrics about food, noise or promptness of nurses’ response to call buttons.
Patient satisfaction is important because it reflects the patients’ perspectives, but he questioned whether some of the metrics, such as a quiet room or good food, would be as important to the patient as an excellent outcome, surviving the episode of care. One of the major findings of the study, though, is that patient satisfaction is a poor measure of quality.
“Patients who have a chronic condition, like heart failure, should go to the large, busy hospitals that treat a lot of patients with heart failure,” Lieberthal said. “That is where they are likely to do the best.”
Much information exists to help patients select a hospital, but many of the indictors may not mean much to patients, Lieberthal explained.
In the paper, he mentions public report cards from the Leapfrog Group and other organizations, as an example. Many well-respected academic medical centers, such as the Ronald Regan UCLA Medical Center in Los Angeles, have not performed well on Leapfrog’s reports.
“The critical piece that is missing from all of these initiatives is that they do not quantify the degree to which different factors contribute to overall quality,” the authors wrote. “In other words, while many analyses focus on quality by hospital type, on improving the processes of care delivery, or on improving health-care outcomes, few prior studies have combined these types of analyses into an overall picture of hospital quality.”
Leapfrog Group declined to comment.
PRIDIT would provide consumers with additional information.
“Our method compares hospitals directly, so that a patient choosing between two or three hospitals can easily compare them and choose the highest-quality facility,” Lieberthal said.
The Centers for Medicare & Medicaid Services (CMS) is beginning to pay hospitals in part from patient satisfaction measures, so they are important.
“Hospitals might be evaluating nurses on satisfaction to maximize their payments from Medicare,” Lieberthal said. “I see a role for nurses in the quality and safety movement to advocate for the measures that most reflect their input in patient care.”
Using PRIDIT, the authors said, could allow clinicians to focus on collecting measures that would have the greatest effect on clinical outcomes.
CMS and commercial insurers could adopt the PRIDIT methodology to existing data. Commercial insurers could set thresholds for a minimum PRIDIT score, which Lieberthal said does not vary significantly over time. However, consumers may not like being steered to facilities that also do not offer good customer satisfaction.
“If providers, such as doctors or nurses or other individuals who treat patients, can use the data that exists about where we get better outcomes, they can direct patients to the places where they are likely to get those high-quality outcomes,” Lieberthal said. “That’s a way for providers to use this information [so patients] do the best they can in the hospital setting.”
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