Patient Registries and Population

A patient registry is an organized system that uses observational study methods to collect uniform data both clinical and other types to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure and that serves predetermined scientific, clinical, or policy purposes. So what are patient registries? and why do we need them?

Advantages of Patient Registries

  • The data are collected in a naturalistic manner, such that the management of patients is determined by the caregiver and patient together and not by the registry protocol.
  • The registry is designed to fulfill specific purposes, and these purposes are defined before collecting and analyzing the data. In other words, the data collection is purpose driven rather than the purpose being data driven (meaning limited to or derived from what is already available in an existing data set).
  • The registry captures data elements with specific and consistent data definitions.
  • The data are collected in a uniform manner for every patient. This consideration refers to both the types of data and the frequency of their collection.
  • The data collected include data derived from and reflective of the clinical status of the patient (e.g., history, examination, laboratory test, or patient-reported data). Registries include the types of data that clinicians would use for the diagnosis and management of patients.
  • At least one element of registry data collection is active, meaning that some data are collected specifically for the purpose of the registry (usually collected from the patient or clinician) rather than inferred from sources that are collected for another purpose (administrative, billing, pharmacy databases, etc.). This definition does not exclude situations where registry data collection is a specific, but not the exclusive, reason data are being collected, such as might be envisioned with future uses of electronic health records, as described in Chapter 15. This definition also does not exclude the incorporation of other data sources. Registries can be enriched by linkage with extant databases

In addition patient registries also helps with risk stratification. Risk stratification is an exciting methodology that assists in identifying outcomes for specific patient populations. Once a population has been identified, clinicians can intervene appropriately to promote a positive result. The ability to risk stratify saves healthcare systems a great deal of time, energy, and money.

Risk stratification takes the guesswork out of helping our patients and helps us preserve fixed resources. It will be an important part of controlling healthcare costs in the future. But most important, in the case of heart failure, it provides our patients the additional assistance needed for a better outcome. After a cohort (risk stratification) has been defined, you will begin to tie metrics and stratifications to the cohort. Each distinct cohort may have its own unique set.

So what do HF readmissions have to do with risk stratification? Everything! By using a risk stratification tool, a provider is able to determine if a patient is at a high risk for readmission and can provide intense focus on providing interventions like those suggested above. However, these interventions require finite resources and precious clinician time.  

By stratifying for a specific group of patients, these limited resources can be directed to the patients where they provide the most value. It makes so much sense! A recent national study by Bradley and others (2012) provides good evidence that some practices implemented by hospitals to reduce readmissions, such as follow-up appointments within 48 to 72 hours of hospital discharge, medication reconciliation by a nurse, involving social workers or case managers, and ensuring outpatient physicians are provided with a discharge summary, really does help prevent readmissions.

With a great deal of thought and input from clinicians, a tool has been developed that has begun to identify patients at high risk of being readmitted. This tool analyzes a number of variables including socioeconomic issues, abnormal lab values, the percentage of left ventricle ejection, a patient’s history of previous readmissions, etc. Patients that need interventions will be flagged as high risk and appropriately treated by clinicians.