Development and testing of a standardized pain interview assessment for use in post-acute care.

Abstract

Pain is highly prevalent among patients in post-acute care (PAC) settings and can affect quality of life, treatment outcomes, and transitions in care. Routine, accurate assessment of pain across settings is important for pain management and care planning; however, existing PAC assessment instruments do not assess patient pain in a standardized manner. We developed and tested a set of pain interview data elements for use across PAC settings (skilled nursing facilities, inpatient rehabilitation facilities, long term care hospitals, home health agencies) as part of a larger effort undertaken by the Centers for Medicare & Medicaid Services to develop standardized assessment data elements to meet the requirements of the IMPACT Act of 2014. The interview assessed six pain constructs: presence; frequency; interference with sleep; interference with rehabilitation therapies [if applicable]; interference with daily activities; worst pain; and pain relief from treatments/medications). A total of 3031 PAC patients at 143 PAC settings (across 14 U.S. geographic/metropolitan areas in 10 states) participated in a national field test of standardized data elements from November 2017 to August 2018. We assessed item response distributions, time to complete interviews, inter-assessor agreement, and, for a subset of patients, change in responses between admission and discharge assessments. We also conducted focus groups with nurse assessors about their experiences administering the items. For patients reporting any pain, average time to complete the pain interview was 3.1min (SD=1.3), and interrater reliability was excellent for all data elements (kappa range: 0.95-0.99). Findings were similar across types of PAC settings. Qualitative data from nurses emphasized ease of administration and high perceived clinical utility. Findings provide support for feasibility of implementing a standardized pain interview assessment in PAC settings. This tool can support tracking of patient needs across settings and interoperability of data in electronic medical records.