Whether you are looking for insights into population health, physician performance for specific health outcomes, or the quality of care your practice provides, you will need to rely on healthcare data sources to inform your assessments.
Healthcare analytics call on a variety of data sources throughout a medical practice to create detailed pictures of the medical, financial, and organizational health of your practice. Data analytics sourced from an EHR system in healthcare can improve how you manage your practice, help identify problems, and optimize workflows to counteract inefficiencies. Knowing how to capture data in a medical practice is an important preliminary step in harnessing data for these purposes.
The practice of using medical data to solve problems in healthcare dates back to the 1960s when Dr. Lawrence Weed, MD, sought to bring medical care more in line with other scientific disciplines.
“The multiplicity of problems the physician must deal with every day constitutes a principal distinguishing feature between a physician’s activities and those of many other scientists,” Weed said in a 2009 Permanente Journal interview.
So, Weed invented the problem-oriented medical record, or POMR, which he later developed into electronic form. He called it the Problem-Oriented Medical Information System (PROMIS), one of the first electronic health records systems created. Weed intended to relieve the burden of physicians tasked with what he saw as the impossible chore of memorizing the entirety of medical knowledge and applying that to several medical problems in a day.
“These two virtues do not arise except where an organized concentration upon a particular subject is possible,” Weed wrote. So, he and programmer Jan R. Shultz developed a system in which the problems and treatment of each patient could be stored and tracked, and that could also deliver epidemiological information on the problems as an informational aid for physicians.
Weed and Shultz were the first to develop how to capture data in a medical practice, a concept that would later be used in pioneering the EHR system.
Examples of Healthcare Data Collection Tools
Contemporary healthcare data collection tools capture data in a medical practice using paper records, manually entered and updated spreadsheets and electronic health records in databases, organized by dashboards.
Your practice or organization may use all these tools, depending on the amount of time you have been in business. Be mindful of the dichotomy between spreadsheets vs. databases in healthcare. The latter is more secure and more accurate.
4 Examples of Healthcare Data Collection Tools
Some examples of how to capture data in a medical practice include electronic health records, claims and billing records, and patient registries — all of which provide the basis for much of the data-driven decision making in healthcare.
- EHR Data — Electronic Health Records are created throughout your practice as your organization takes on new patients, schedules appointments, and arranges for prescriptions or care. You will also create this data from daily financial operations, billing, claims, and insurance records. Administrative clinical data including demographics, progress notes, problems, medications, vital signs, past medical history, immunizations, laboratory data and radiology reports all constitute EHR data.
- Claims and Billing Data — Health claims and billing data is obtained and aggregated by the practice for submission to health care payers. Age, sex, employment status, diagnosis and procedure codes are all examples of claims data collected by a practice.
“The good thing about claims data is that, like other medical records, they come directly from notes made by the health care provider, and the information is recorded at the time patient sees the doctor. Also, because of the large sample size of claims data, researchers can analyze groups of patients with rare illnesses and medical conditions,” the National Library of Medicine notes.
- Patient registries— Patient registries are collections of standardized information about a group of patients who share a condition or experience. Typically created by researchers, patient registries exist for a variety of diseases, both rare and chronic, including cancer, diabetes, cystic fibrosis, acute coronary syndrome, and arthritis.
Registries are used to recruit people for clinical trials to learn about specific conditions and diseases, to develop therapies or to learn about population behavior. They can also be used to monitor outcomes and study best practices in care, according to the National Library of Medicine. “PPRs may also pursue a specific research question or conduct ongoing data collection to answer a variety of existing and emerging research questions. Several PPRs have biobanks, or repositories, where patients can provide samples of blood or tissue to be used in research. Other patient advocacy organizations, such as the TMJ Association, use their registry as a recruitment vehicle for existing clinical trials, inviting members of the TMJ community whose profile matches a trial protocol,” the NLM states.
Patient registries often begin as patient support or advocacy groups to provide data that can better inform researchers and clinicians. This also offers information that can assist fellow patients and their families in decision making. PatientsLikeMe, for example, was founded by the Heywood family to search for information that might improve the life of Stephen Haywood, diagnosed by ALS. The organization now includes about 1,200 disease registries.
- Population health data — Population health data include statistics, measures, and indicators of the state of and influences on the health of a specific population. Patient race and ethnicity data is already likely collected by electronic health records systems in your practice.
Many EHRs are already set up to collect this data if staff are not already properly trained on how to ask for this information. Practices can use this information to develop and carry out quality initiatives improving health and to address health inequities.
Methods and Best Practices for Collecting Patient Data
Collecting patient data for population health analytics can provide effective insight into your community’s health needs. But be sure you know how to capture data in a medical practice in a secure and compliant way.
Some data collection practices, such as the once-widespread use of social security numbers as unique patient identifiers, is increasingly problematic for patients. Many are no longer comfortable sharing this information in a healthcare setting, as the National Association of Healthcare Access Management notes in its Best Practice Recommendations for the Collection of Key Data Attributes, that outlines how to capture data in a medical practice.
Collecting Patient Data in Your Existing Systems
Whether your rule of thumb is to update patient information annually, or only whenever a change in their health warrants updating the records, simplicity and accuracy are qualities to strive for whenever new information is added.
Documenting patient information with the proper workflows and templates is also an important habit to encourage and observe. Workflow workarounds, such as copying past patient notes into a new entry to serve as the draft for the update, for instance, has been shown to lead to confusion and medical errors. Practices should discourage such workarounds both by establishing a policy and by streamlining workflows to reduce the need for workaround solutions.
For patient records, the matter of secure storage remains an important concern. The Health Insurance Portability and Accountability Act of 1996 (HIPAA)’s Security Rule establishes a national set of security standards for protecting electronic health information.
Under the rule, covered entities, including medical practices, must:
- Ensure the confidentiality, integrity, and availability of all electronic protected health information (e-PHI) they create, receive, maintain or transmit;
- Identify and protect against reasonably anticipated threats to the security or integrity of the information;
- Protect against reasonably anticipated, impermissible uses or disclosures; and
- Ensure compliance by their workforce.
Safeguards for e-PHI span the following spheres:
- Administrative – Establish security management and security personnel)
- Physical – Limit access, implement policies and procedures for how to capture data in a medical practice, or specifying access to electronic media)
- Technical – Audit controls and transmission security
Whatever EHR solution you choose, make sure you have established a business associate agreement (BAA) with the vendor. HIPAA-covered entities are required to enter into business associate agreements (BAAs) with any third party that handles protected health information (PHI). BAAs are formal agreements with third parties that they will maintain PHI security and overall HIPAA compliance. The process assumes the covered entity is responsible for having properly vetted the third party in question in addition to establishing the formal agreement.
Analyzing Your Population Level Data
Once you have collected the data, it can be analyzed to better improve your practice, and that does not necessarily have to happen one patient at a time.
Population health data is, as discussed, the use of patient information to improve health at the population level rather than with an individual patient. Assessing information such as social circumstances, environmental exposures, and behavior patterns as it affects patient health can point providers in the direction of disease prevention or the promotion of healthier lifestyles.
Economic factors can also be tracked with patient data collection. Knowing a patient’s access to housing can inform how difficult it may be to take medication regularly. Someone with limited access to healthy food will find it more difficult to control their blood pressure or manage diabetes. Knowing these sorts of details can allow doctors to approach care with strategies that are more likely to succeed.
EHR dashboards geared toward patient information showing such population health insights can influence doctors’ planning of care.
Healthcare Analytics Examples: Use Cases for Your Practice Data
Once you successfully capture the data, here is how you can make use of it:
- Forecasting patient demand – A look at weekly and monthly patient records can provide insight into when your practice is likely to see a surge in patient visits. It can also inform which services your patients will be seeking out most often.
- Monitoring real-time for resource planning – Figure out ahead of time how many providers you will need on hand and how much personal protective equipment you are going to need to meet your patient demand.
- Better managing of population health – Knowing many of your patients hail from an aging community will allow you to plan to provide gerontological care, and to have third party resources available.
- Speeding up submission of claims– Claims submissions filed sooner will help you get paid faster.
- Reducing denied claims – Fewer denied claims, by virtue of the right documentation provided promptly, will increase payments, and revenue.
Get the Most Benefit from Your Healthcare Data with Medical Advantage’s Solutions
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