{"doi":"10.1111/jgs.16974","title":"Validation of the Minimum Data Set Items on Falls and Injury in Two Long‐Stay Facilities","abstract":"Falls are common among nursing home (NH) residents with 4% to 11% of falls resulting in fracture or other serious injury.1, 2 Injurious falls have a higher incidence and mortality in NH residents than falls among community dwellers.1, 3, 4 Therefore, it is important to accurately identify falls in NH residents. The Minimum Data Set (MDS) was developed as a means to assess the health status of NH residents.5 In 2010, the MDS v3.0 was deployed in the United States, with considerable changes in how falls and injuries are assessed.6 The purpose of our study was to validate the MDS v3.0 items on falls and injuries with chart review in two facilities. Our study was conducted in two long-term care facilities (MA&NC). Both facilities employ software that auto-populates items using the prior MDS assessment, including falls reporting. Eligible residents had at least two valid MDS assessments between January 2016 and April 2019. From the first facility we randomly selected 50 residents with an MDS indicator for an injurious fall, 50 with an MDS indicator for a fall without injury, and 50 without fall. Only two major injuries were initially selected, and so we identified an additional 23 residents with an indicator of major or minor injury. From the second facility, we sampled all residents with an injurious fall indicator (n = 10), all residents with a fall without injury (n = 18), and a random sample of 50 residents without fall. The MDS v3.0 queries whether a fall has occurred since admission or since the last MDS assessment. If a fall occurred, staff categorize the number of falls with no injury, minor injury, or major injury. A major injury is defined as falls resulting in fracture, dislocation, concussion, or intracranial hemorrhage. Minor injuries are defined as falls resulting in pain, or a skin tear, abrasion, laceration, bruise, hematoma, or sprain. Blinded, trained abstractors (Joel Mintz, Emily J. Hecker, and Alexandra Lee) conducted the chart review. For each resident, the abstractor reviewed all provider and nursing notes in the electronic medical record between the relevant MDS assessments. Pain was operationalized as lasting >24 h, required analgesia medications, or required evaluation by a provider. All falls and injuries were recorded in a REDCap database. A second abstractor (Cathleen Colón-Emeric) reviewed 8 charts with good concordance (Cohen's Kappa = 0.81) Residents were then categorized as having one or more fall, fall with minor injury, and fall with major injury. Fall and injury agreement between the MDS and chart review was assessed using Cohen's Kappa test. Sensitivity, specificity and positive predictive value (PPV) were calculated. In total, we included 251 residents. Mean age was 89.4 years (±8.0), 68.1% were female, and 8.4% were non-white. The average time between MDS assessments was 108 days (±46). Our chart review identified 124 fallers, of whom 20 had one or more major injuries and 85 had one or more minor injuries. The most common major injury was fracture (n = 18). The most common minor injuries were pain (n = 56) and bruising (n = 44). Table 1 shows agreement between falls and injury as assessed by the MDS and chart review. Kappa agreement was low for all comparisons: 0.44 for falls, 0.30 for major injury, and 0.24 for minor injury. The sensitivity, specificity, and PPV of the MDS to identify falls were 0.78, 0.66, and 0.69, respectively. For major injuries, the sensitivity, specificity, and PPV were 0.40, 0.93, and 0.33. For minor injuries, the sensitivity, specificity, and PPV were 0.39, 0.84, and 0.55. Results were similar between the two facilities. A previous study validating the MDS v2.0 found good specificity (97%) but low sensitivity (53%) to identify falls.7 To the best of our knowledge, no studies have validated MDS v3.0 fall or injury items. We found the sensitivity and specificity of the MDS v3.0 to identify falls to be quite modest. Falls with major injuries had a greater specificity tha","journal":"Journal of the American Geriatrics Society","year":2020,"id":84377,"datarank":0.5447081252994757,"base_score":2.3978952727983707,"endowment":2.3978952727983707,"self_citation_contribution":0.3596842909197557,"citation_network_contribution":0.18502383437972,"self_endowment_contribution":0.3596842909197557,"citer_contribution":0.18502383437972,"corpus_percentile":64.29952811943993,"corpus_rank":4616,"citation_count":10,"citer_count":4,"citers_with_citation_signal":3,"citers_with_endowment":3,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.762,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":452,"name":"Alexandra J. Lee","orcid":"0000-0002-0208-3730","position":1,"is_corresponding":false},{"id":433381,"name":"Meryl Gold","orcid":null,"position":2,"is_corresponding":false},{"id":433382,"name":"Emily J. Hecker","orcid":null,"position":3,"is_corresponding":false},{"id":373358,"name":"Cathleen Colón‐Emeric","orcid":"0000-0001-7681-8624","position":4,"is_corresponding":false},{"id":273886,"name":"Sarah D. Berry","orcid":"0000-0002-3793-4187","position":5,"is_corresponding":false},{"id":432754,"name":"Joel A. Mintz","orcid":"0000-0002-8121-1736","position":0,"is_corresponding":true}],"reference_count":8,"raw_metadata":null,"created_at":"2026-07-18T21:54:50.827092Z","pmid":"33615432","pmcid":"PMC8136143","fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}