Post-op Crowd Sourcing Health Data Via Text-messaging

Acute Injuries Knee, Neurosurgery, Opioid Use, Orthopedic Surgery, Surgery

Quality Improvement, Prescription Use, Patient Experience, SMS Messaging, Crowd Sourcing

The Center for Disease Control has labeled the opioid prescription drug crisis an epidemic in the United States and recently this epidemic has been named a public health emergency. Various medical and surgical societies have begun to release general opioid prescribing guidelines for providers addressing acute pain, but these do not highlight the patient perspective or experience. Identifying an acceptable opioid dose and duration has remained a challenge and is a nuanced process. Though policy and provider driven changes may begin to augment practice, these avenues may miss a crucial perspective; the patient's.

This is a quality improvement project aimed at building upon prior telephone-based patient follow-up. The research team will be launching a text messaging interface to collect and describe patient pain, functional status, and opioid usage with patients undergoing elective surgical procedures within the departments of orthopaedics and sports medicine, as well as patients treated in neurosurgery, general surgery, and the ED who own a mobile phone and can receive SMS text messaging (as measured by pain scale, patient reported functional status, and proportion of opioids used). Additionally, this project aims to evaluate the current standard of care of prescribing opioids to patients among orthopedic surgeons and emergency medicine providers for acute pain. BACKGROUND The study team has shown the ability of gathering patient level data from telephone follow up to guide physician behavior. In recent work, providing orthopaedic surgeons with data on patients' unused prescribed opioids has changed practice - patients now reporting a change from twenty unused pills down to seven unused pills. Though effective, telephone follow up is laborious and time consuming. The researchers seek to test an alternative approach for a rapid, scalable means of engaging patients and gathering patient level data to help inform provider practice. Text messaging offers a unique opportunity to quickly capture, analyze, and understand the patient experience. The research team has demonstrated the successes of communicating with patients via text-messaging by guiding patients through pre- and postoperative recovery via the program Engaged Recovery at Penn (ERAP). This program has enrolled over 900 patients across surgical specialties with automated text-based reminders. The researchers will investigate the intersection of digital patient centered communication, acute pain, and consumption of prescribed opioids to ultimately help inform providers and health systems. METHODS The study team will contact adult patients (age ≥18) undergoing elective surgical procedures within the departments of orthopaedics, sports medicine, and neurosurgery, as well as patients undergoing procedures in general surgery and the ED who own a mobile phone and can receive SMS text messaging at the University of Pennsylvania or Penn Presbyterian Medical Center. The researchers will build upon previous work by Dr. Delgado in which patients were approached for follow up data collection via telephone communication and translate the telephone script into a functional and approachable text messaging script. The researchers will work to build an automated bi-directional text script hosted on a secure web portal. The research team will test the ability to engage patients in these departments, gather data, and measure satisfaction with the automated text-messaging system. Data collected through the online texting portal will be used to demonstrate the ability of bi-directional texting to enhance data collection and then the researchers will utilize this data to develop, implement, and evaluate the use of EMR defaults for opioid prescribing for specific surgical procedures or acute painful conditions. In addition, the study team will build and deploy an online survey containing the script questions in order to test an alternative to capturing patient data. Using block randomization, a subset of patients will receive either 1) a link to the online survey or 2) the bidirectional text messing script. Patient questions will not change but the method of data collection will test which approach yields a higher response rate. The study team will collect both response and completion rates and evaluate which data collection method is more effective for gathering data using an automated system. Insights gained from this comparison will be used to develop the automated text system and methodology.

United States

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