Potential effect of authorization bias on medical record research

S J Jacobsen1, Z Xia, M E Campion

  • 1Section of Clinical Epidemiology, Mayo Clinic Rochester, Minnesota 55905, USA.

Abstract

Insights

New Minnesota laws requiring patient authorization for medical record research may introduce significant bias. This could impact studies on disease causes and outcomes, necessitating clinician and legislator awareness of potential research access restrictions.

Area of Science:

  • Medical Informatics
  • Public Health Policy
  • Biostatistics

Background:

  • Recent Minnesota statutes mandate prior patient authorization for using medical records in research for care post-January 1, 1997.
  • This legislation impacts the accessibility of historical patient data for scientific inquiry.

Purpose of the Study:

  • To evaluate the effect of new Minnesota statutes on patient authorization for medical record research.
  • To identify potential biases introduced by these access restrictions.

Main Methods:

  • A stratified random sample of Mayo Clinic patients from 1994-1996 was surveyed for authorization.
  • Demographic, diagnostic, and utilization data were compared between patients who provided and refused authorization.

Main Results:

  • The refusal rate for authorization was 3.2% (or 20.7% if non-responders are included).
  • Younger patients, women, and those with sensitive diagnoses were more likely to refuse.
  • Distant rural patients were less likely to refuse than local residents.

Conclusions:

  • Laws requiring written patient authorization can create substantial biases in etiologic and outcome research.
  • The direction and magnitude of bias may vary depending on the research topic.
  • Clinicians must inform patients and legislators about the risks of restricted medical record access for research.

Related Concept Videos

The Availability Heuristic01:08

The Availability Heuristic

A heuristic is a general problem-solving framework (Tversky & Kahneman, 1974). You can think of these as mental shortcuts that are used to solve problems. Different types of heuristics are used in different types of situations, and the impulse to use a heuristic occurs when one of five conditions is met (Pratkanis, 1989):
Bias01:22

Bias

Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected or encouraged over others in sampling or testing. Bias can occur during any research phase, including study design, data collection, analysis, and publication.
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
Purpose of Health Records I01:11

Purpose of Health Records I

The vital purpose of health records is to provide a complete and accurate account of a patient's medical history, including communication, diagnostic and therapeutic orders, care planning, research, and quality review.
Here's a breakdown of how health records serve these purposes:
Purpose of Health Records II01:19

Purpose of Health Records II

Health records serve various essential purposes in the healthcare system. Here are some key purposes:
Ethical Standards II01:23

Ethical Standards II

Ethical standards are the backbone of nursing practice, guiding nurses as they interact with patients, families, and colleagues. These standards are crucial for providing safe, empathetic care centered on the patient's needs.
Nurses are entrusted with upholding various ethical principles and standards. Nurses forge solid therapeutic relationships using trust, empathy, autonomy, confidentiality, and professional competence.
Confidentiality is crucial, embodying respect for individual privacy and...
Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is: