Joint and Soft Tissue Injection

Injection techniques are helpful for diagnosis and therapy in a wide variety of musculoskeletal conditions. Diagnostic indications include the aspiration of fluid for analysis and the assessment of pain relief and increased range of motion as a diagnostic tool. Therapeutic indications include the delivery of local anaesthetics for pain relief and the delivery of corticosteroids for suppression of inflammation. Side effects are few; but may include tendon rupture; infection; steroid flare; hypopigmentation; and soft tissue atrophy. Injection technique requires knowledge of anatomy of the targeted area and a thorough understanding of the agents used. In this overview; the indications; contraindications; potential side effects; timing; proper technique; necessary materials; pharmaceuticals used and their actions; and post-procedure care of patients are presented

Diagnostic and Therapeutic Injection of the Shoulder Region

The shoulder is the site of multiple injuries and inflammatory conditions that lend themselves to diagnostic and therapeutic injection. Joint injection should be considered after other therapeutic interventions such as non-steroidal anti-inflammatory drugs; physical therapy; and activity-modification have been tried. Indications for glenohumeral joint injection include osteoarthritis; adhesive capsulitis; and rheumatoid arthritis. For the acromioclavicular joint; injection may be used for diagnosis and treatment of osteoarthritis and distal clavicular osteolysis. Subacromial injections are useful for a range of conditions including adhesive capsulitis; subdeltoid bursitis; impingement syndrome; and rotator cuff tendinosis. Scapulothoracic injections are reserved for inflammation of the involved bursa. Persistent pain related to inflammatory conditions of the long head of the biceps responds well to injection in the region. The proper technique; choice and quantity of pharmaceuticals; and appropriate follow-up are essential for effective outcomes

Patient care staffing patterns and roles in community-based family practices.

OBJECTIVES: Our study describes patient care staff patterns and roles in community-based family practices. STUDY DESIGN: We used a multimethod comparative case study design that included detailed descriptive field notes of the office environment of 18 family practices and of 1637 clinical encounters, as well as in-depth interviews of practice staff and physicians. Systematic analysis of these data provided detailed descriptions of patient care staff patterns and functions. POPULATION: We included physicians and staff in 18 community-based Nebraska family practices. RESULTS: Practices are staffed with a range of clinical personnel, including registered nurses, licensed practical nurses, certified medical assistants, radiology technicians, and trained and untrained medical assistants. Each of these has specific educational preparation that potentially qualifies them for different patient care roles; however, staff roles were determined primarily by local needs and physician expectations rather than by education, training, or licensure. Staffing patterns varied greatly; the majority of practices employed at least one registered nurse (10 of 18), one licensed practical nurse (5), or both (4). Still, the overall majority of practices used non-nursing personnel as the predominate patient care staff. Patient care staff-to-clinician ratios ranged from a low of 0.5 to a high of 3.3. CONCLUSIONS: Many recent recommendations about collaborative models of clinical care seem problematic when put into a context of the findings of current staffing patterns and use of personnel in family practices. Staff members often fulfill roles independent of training. Staff leadership is also potentially important for designing effective collaborative care models; however, we found leadership only occurred with the approval of clinic authorities. These practical issues are rarely addressed in normative recommendations about system change and intervention. Our findings indicate that there are considerable opportunities for better use of the nursing and other patient care staff in the delivery of clinical services. Developing a collaborative practice model should include formalizing expectations of staff to reflect training and experience, and explicitly configuring staff to meet the needs, values, and goals of a practice.

Academic-community linkages: community-based training for family physicians.

BACKGROUND: Community-based curricular experiences have been proposed to fulfill the graduate training needs of future family physicians. Are such experiences feasible? How can such experiences be started? What outcomes can be expected? METHODS: We describe 15 years' experience with community-based training in family practice graduate medical education at UMDNJ-Robert Wood Johnson Medical School. We also describe the process of creating academic-community linkages using stakeholder management and the resultant programs that evolved to fulfill specific training requirements. RESULTS: Five of the curricular programs designed are described, four of which were successful. Community-based training enhanced recruitment of students of minority background into the residency, and a high proportion of residency graduates have established practices in communities with underserved populations. CONCLUSIONS: Community-based training of family physicians is a feasible and effective means of addressing unmet health needs of communities served by graduate medical education programs and their related health care institutions.

Family practice graduate medical education and hospitals' patient care costs in New Jersey.

BACKGROUND: More generalists are needed for the American health care system. Will training these practitioners add to hospital costs? Although graduate medical education has been shown to add to hospital patient care costs, the authors questioned whether this were true for the hospital training of family physicians. METHOD: Based on data supplied by 12 participating New Jersey hospitals with family practice residencies, inpatients in 1991 were separated into three categories by the teaching status of their attending physicians: family practice, other teaching, non-teaching. The hospitals were stratified into two types for analysis: seven community and five multiresidency hospitals. Average cost (per case-mix--neutral case) was found for each category of patients within medical, surgical, pediatric, and obstetrical classes. RESULTS: Among community teaching hospitals, the mean case-mix--adjusted cost per case for inpatients associated with family practice training was 6.3% less than that for inpatients with an equivalent case mix not associated with family practice training. Among multiresidency teaching hospitals, there was no difference between mean costs for inpatients associated with family practice training and non-teaching patients. The mean cost for inpatients associated with graduate medical training other than family practice was 8% higher than that for non-teaching inpatients. CONCLUSION: These findings suggest that family practice residencies do not add to the direct inpatient costs of teaching hospitals, and in certain instances may even reduce hospital patient care costs. In times of increasing cost consciousness in health care and medical education, this provides a further rationale for institutions to sponsor graduate training in family practice.

Display of small-area variation in health-related data: a methodology using resistant statistics.

Health care planning requires characterization of the population to be served. Examination of available demographic and epidemiologic data is one early step in this process. However, aggregate data for the entire geographic area of concern often fail to reveal important differences among geographically defined sub-populations--differences that influence the form an effective delivery system should take. We present a methodology based on exploratory data analysis (EDA) techniques that we have found useful in examining health-related data for our ambulatory care catchment area. Our examples use three population characteristics that have major implications for health care planning for the elderly: 1970-1980 change in population aged 65+; the percent of the population aged 65+ below poverty level; and the percent of single-person households among households with one or more persons aged 65+. With these data for the 25 municipalities of Middlesex County, New Jersey, we illustrate a two-step process: (1) the construction of stem-and-leaf displays that permit examination of a data distribution for asymmetry, concentrations around specific values, gaps in values, and outliers; and (2) the use of the median, the fourth-spread, and other information from the stem-and-leaf display in the systematic selection of data value classes to be given distinct shadings on a map of the selected geographic area. Discussion emphasizes the usefulness of graphic display of data in detecting similarities and unusual data values. Comparison of maps based on the EDA techniques and maps based on several traditional methods of value classing for the same data illustrates the influence of classing choices on the interpretation of cartographic displays of health-related data.