Could Your Organization’s Outcomes Improve?
If you felt disappointed with your healthcare organization’s last round of Examples of Quality Measure Outcomes, Health Catalyst can help drive improvement. Please contact us to learn more about specific ways we can help you achieve higher scores in these areas. I have begun to ask myself more and more about this data that is collected: how much information does a small doctors’ practice generate in a month or a year? Much of the information is stored electronically, and no longer sits on a shelf with innumerable other active and inactive files. This manufactured data reveals details that a doctor or other staff needs in order to fill in a better picture of each of us.
According to the Agency for Healthcare Research and Quality (AHRQ), a quality measure is a method used to compare and assess healthcare organizations. The AHRQ also states that the Donabedien Model, named for the physician and researcher who created it, divides quality measurements into three classifications. These include outcome, process, and structural measures.
This classification of quality measurements assesses the impact of the healthcare intervention on the patient. As an example, a hospital might report how many patients died as a direct result of surgery and the number who acquired an infection in the hospital. However, it’s important to remember that providers cannot control every factor. For example, the organization may serve mainly elderly people more prone to catch an infection in the first place.
One way to manage this variable is to employ several risk-adjustment methods. These are mathematical calculations that adjust scoring based on the prominent characteristics of the patient population. This helps healthcare organizations avoid reporting inaccurate information about the quality of their services.
This aspect of quality assessment records the steps an organization took to care for patients along with the effectiveness of those measures. It includes helping currently healthy people maintain their status along with the processes used to help people with a diagnosed condition improve. Process measurement typically records accepted recommendations for patient health management in a clinic or hospital setting.
A prime example of the above is the number of patients who receive depression screening, mammograms, or well-child preventive care visits every year. When the public views healthcare quality data, it typically comes from a formal process measurement study. This method informs patients of the type of care they can expect for a specific medical condition. Having access to this type of information can affect patient follow-through and outcome measurements in a positive way.
A structural measure is one that can provide healthcare consumers with data regarding a provider’s processes, capacity, and systems so they can choose whether that organization is right for them. One of the most obvious structural measures is the number of patients each individual physician has on his or her caseload. This indicates to patients how long they might need to wait to schedule an appointment or even in the waiting room at the office.
Another important structural measurement is the number of doctors with board certification and other forms of advanced recognition. This can help patients choose a specialist as well as feel more confident in the skills of their provider. Whether a healthcare organization uses electronic or paper medical records is yet another example of a structural measurement.
Who Determines Outcome Measurements?
The Department of Health and Human Services (HHS) and the Centers for Medicare and Medicaid Services (CMS) jointly initiate measurements that help to determine quality at healthcare organizations across the country. When creating outcome measurements, the HHS and CMS look for indications of effective, efficient, equitable, patient-centered, and safe care delivered in a timely fashion.
In 2016, the CMS created a hospital star rating system. Examples of quality measure outcomes include:
- Patient Experiences
- Safety of care
- Effectiveness of care
- Efficient use of medical imaging
- Timeliness of care
The first four categories have an importance weight of 22 percent each for a total of 88 percent of the star rating. The last three make up 12 percent of the rating with a four percent importance rating for each one.
Many Americans are cautious about having their data readily available to outside persons. However, many researchers want to find patterns in large numbers. For these individuals and groups, information that explains certain health conditions, reproductive outcome and overall quality of life produces a more predictive picture and thus a greater realization of where and even when health professionals may be needed. Healthcare data is a treasure trove of facts and patterns that can answer complex questions. Maybe you have seen an episode of House where a patient has symptoms that don’t fit into any known disease or ailment checklist. Dr. House ends up torturing his residents to find what the collection of symptom adds up to. To be tapped into vast amounts of data that can show a continued history from before sickness to what cured or alleviated a person’s condition could prove to be helpful to someone else hundreds of miles removed.
What I find even more fascinating than being properly diagnosed at the time of service is that my doctors could have vital information available to them about unique maladies that could more quickly be identified and tackled. Sorry Dr. House, your residents would not stuck in a medical library with dozens of books in front of them, but in front of a computer promptly finding out a prognosis that fits me perfectly.
Though the future of all the data that has been amassed from our visits to the doctors no longer sits stale on shelves or misdiagnosed because of its distinctive qualities, healthcare and its professionals will have more to help them combat and maybe even prevent failing health issues.