Chronic Pain: Database Management Approach

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Table of Contents

Introduction
Relevant Data
Database Structure
Database Usage
Conclusion
References

Introduction

Chronic, or persistent, pain is a prevalent issue in clinical patients. It can stem from a multitude of causes, which range from consequences of trauma or surgery to particular diseases or being caused by treatment (Treede et. al., 2015). It is a significant reason for a reduced quality of life in patients (Edwards et al., 2016). Therefore, the management of chronic pain is a crucial element of patient care. Although a variety of treatments exist for this purpose, there is significant inter-patient variability in their outcomes (Edwards et al., 2016). Furthermore, “long-term administration of analgesics such as non-steroidal anti-inflammatory drugs (NSAIDs) and opioids involves risks of organ damage, overdose, and, in some cases, drug dependence and misuse syndromes” (Edwards et al., 2016). As a consequence of these factors, a large number of variables need to be considered for improving the management of chronic pain in patients.

Relevant Data

To implement a database management approach to investigating, recording, and, ultimately, treating pain, one needs a design that incorporates as many factors that affect pain and pain treatment. A patient’s history of diagnoses and pain prescriptions, and history of responses to such, is crucial for establishing a factual base for future decisions. A diagnosis history is relevant because different illnesses cause different types of pain that respond best to different treatments (Stanos et al., 2016). A history of previously used methods of pain treatment and the patient’s response to them can be used when assessing whether a method should be adjusted or a new one assigned (Centers for Disease Control, 2016). Furthermore, this information can be useful to assess possible drug-drug interactions that can affect the ultimate choice of medication (Moore, Pollack, & Butkerait, 2015). All of these data need to be assembled in a convenient, easily searchable, and sortable database structure to facilitate the visualization of their relationships and selection of the appropriate treatment.

Database Structure

A database approach to managing patients’ chronic pain would require accounting for several factors that fall into four general categories. The first includes the initial cause of pain, consisting of primarily structured data of diagnoses and dates. The second category is comprised of both structured and unstructured data describing the patient’s history of pain medication and treatment methods. The third category, primarily unstructured, includes factors that are not necessarily related to diagnosis or treatment history, but affect the patient’s individual indications or contraindications. Finally, a patient’s general biometrics, such as his or her age, weight, and sex, can all be relevant for prescribing treatment.

Figure 1. Proposed database structure.

Figure 1 visualizes the four categories with one sample entity each. Elaborating on each entity and attribute:

Biometrics is the biometric data from the patient’s EHR. As these data are pulled from the EHR, their operational definitions are determined by what is already present in the database, thus following existing standards and conventions.

- The date of birth is used to calculate the patient’s age, an important factor for prescribing pain treatment.

- Weight is important to determine the appropriate dosage when prescribing medication.
Diagnosis contains the data on one of the patient’s diagnoses, pulled from his or her EHR. Of particular importance are:

- The name refers to the diagnosis’ name and code, linking to the diagnosis database.

- The date is the date when the diagnosis was given. In all tables, the date should inherit its format from the currently used EHR system; if that is impossible, a standard YYYY-MM-DD format should be used.
- The prescription contains the name and ID of the specific treatment or medication prescribed for the diagnosis, linking to the treatment or medication database as appropriate.
The Treatment entity refers to a particular treatment or medication prescribed to the patient as a means of managing his or her chronic pain.

- The treatment’s name refers to its name and ID, linking to the medication or treatment database, as appropriate.

- Start date and end date refer to the date range when the treatment or medication was active. This is relevant to estimate the development of a patient’s tolerance or possible drug interactions during that time.
- Comment contains a physician’s note concerning the patient’s response to the treatment. This field is unstructured and can include information on tolerance, drug interactions, or other details of the patient’s response to the treatment.
The miscellaneous factors table is less structured than the other three. It contains information on various factors that can affect what treatments or medications can be prescribed to manage a patient’s pain. These factors can include a developed tolerance, known allergies, known drug interactions, or behavioral factors such as dependence and misuse.
- The name and date fields are necessary to identify each factor and the time when it was recorded. Since these factors are not necessarily diagnoses, the name field may not contain a linking ID.
- The positive and negative indications are IDs and names linking to specific treatments and medications in the corresponding database. These fields are used by the health care provider when choosing an appropriate method for managing the patient’s pain.
- The comment field contains the physician’s note on the factor in question. Any clarifications or comments that can further affect the should be recorded in this field.

Database Usage

This database approach should be whenever a patient suffering from chronic pain needs to have his or her methods of pain treatment updated. It can make use of cross-linking between its three tables (note that dates and medication/treatment IDs are present in all of them). This allows the specialist to easily visualize the relationships between past diagnoses, history of pain, and miscellaneous factors relevant to this choice. Furthermore, each table can be explored individually if more detailed evidence is necessary.

Conclusion

Chronic pain is a major clinical problem that affects a significant number of patients. A large selection of treatments exists to help manage it, and selecting one that is optimal for each individual patient is a complex task that requires considering a multitude of factors. These factors can include the patient’s diagnoses explaining the initial causes of pain, past and current methods of pain treatment and response to them, biometric data, and a large set of information classed as miscellaneous. In organizing and visualizing these factors and the relations between them, a database management approach may bring significant improvements. Therefore, a database can be designed, incorporating information related to a patient’s history of pain and pain treatment methods. Such a database would connect with the patient’s EHR to pull existing data and provide fields for the entry of new data. The usage of this database design should facilitate choosing an appropriate method of treating an individual patient’s chronic pain.

References

Centers for Disease Control and Prevention. (2016). Guideline for prescribing opioids for chronic pain. Journal of Pain & Palliative Care Pharmacotherapy, 30(2), 138-140. Web.

Edwards, R. R., Dworkin, R. H., Turk, D. C., Angst, M. S., Dionne, R., Freeman, R., … Yarnitsky, D. (2016). Patient phenotyping in clinical trials of chronic pain treatments. PAIN, 157(9), 1851-1871. Web.

Moore, N., Pollack, C., & Butkerait, P. (2015). Adverse drug reactions and drug-drug interactions with over-the-counter NSAIDs.Therapeutics and Clinical Risk Management, 11, 1061-1075. Web.

Stanos, S., Brodsky, M., Argoff, C., Clauw, D. J., D’Arcy, Y., Donevan, S., … Watt, S. (2016). Rethinking chronic pain in a primary care setting. Postgraduate Medicine, 128(5), 502-515. Web.

Treede, R. D., Rief, W., Barke, A., Aziz, Q., Bennett, M. I., Benoliel, R., … Wang, S. J. (2015). A classification of chronic pain for ICD-11.PAIN, 156(6), 1003-1007. Web.

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Chronic Pain: Database Management Approach

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