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Shoulder Shoulder osteoarthritis (OA) is common. Primary shoulder OA is the most common form. The most common type of secondary shoulder OA is rotator cuff arthropathy and is believed to be related to a decoupling of forces about the humeral head. Typical presentation is activity-related shoulder pain and loss of shoulder range of motion. Physical exam should include an assessment of the rotator cuff and axillary nerve. Standard radiographs are often sufficient to make diagnosis, but cross-sectional imaging may be indicated to identify bone loss (CT) or soft tissue deficiencies (MRI/ultrasound). Nonoperative care can include physical therapy, pharmacotherapy, and intra-articular injections (cortisone and hyaluronic acid), but evidence for or against these treatments is limited. Surgical management of end-stage shoulder OA includes arthroscopic debridement, interposition arthroplasty (glenoid resurfacing), humeral head resurfacing, hemiarthroplasty, anatomic total shoulder arthroplasty, and, in low demand patients with a deficient rotator cuff, reverse total shoulder arthroplasty. In young patients with end-stage shoulder OA, arthroplasty has high failure rates secondary to either glenoid erosion (hemiarthroplasty) or glenoid component loosening (anatomic total shoulder arthroplasty). For older patients with end-stage shoulder OA and an intact rotator cuff, anatomic total shoulder arthroplasty is recommended.

1. Precision medicine, or what patients and the media often call personalized medicine, aims to utilize molecular profiles of patient biospecimens and increasingly precise outcome metrics from diverse biosensors to more accurately diagnose a disease, tailor the therapy a patient receives, and monitor response. 2. In order to accomplish the goals of precision medicine in osteoarthritis, several key components of biomedical research (target identification, marker identification, molecular mechanisms) and clinical medicine (treatment, diagnosis, health outcomes) must be seamlessly integrated across several data repositories (clinical records, biospecimen, -omics databases) and analyzed using integrative data mining and iterative learning strategies. 3. A clinically meaningful and feasible strategy is required for identifying OA phenotypes for targeted treatment. 4. The OA Data Integration Platform (OADIP) provides comprehensive, expert curated clinical and molecular data repository across OA. Advances in molecular profiling, interoperability, integration, and exchange of data combined with machine learning techniques will enable comprehensive signatures for OA subtypes to be identified and targeted for treatment and discovery. 5. The feasibility and reality of precision medicine for OA are on the horizon as we strive to provide the right care to the right patient at the right time.