ELECTRONIC HEALTH RECORDS (EHRs) AND PATIENT WORK INFORMATION

A teenage male goes to a hospital emergency department (ED) in mid-August with flu-like symptoms. The intake demographic data include date of birth, gender, home address, work address, current occupation, and current industry, and whether the patient was working when the symptoms occurred. The ED physician interviews the patient regarding the symptoms and finds that he is also having excessive salivation and perspiration and notes the youth’s current occupation is farm worker and current industry is agriculture. The physician asks about the activities of the teen prior to the onset of the symptoms and learns that he was picking fresh fruit at a nearby apple orchard. Based on his symptoms, work activities, and laboratory results the physician diagnoses acute pesticide poisoning. The electronic health record (EHR) system indicates that pesticide poisonings are a reportable condition within the state and offers a reporting form pre-populated with the patient data, healthcare and provider data, patient test results, and metadata. An info tab provides a brief explanation of the distinctions between confirmed, probable, or possible pesticide poisoning. The physician marks the case as probable and continues to treat the teen for the likely poisoning. The physician clicks a button, signaling the ED administration to send the pre-populated reporting form to the state health department via secure email. The health department looks for similar EHR reports from other hospitals in the same area and identifies five additional “probable” or “possible” poisoning patients at local orchards. Based on these reports, the health department contacts the state department of agriculture and initiates an investigation of pesticide application and exposure at local apple orchards.

A Portuguese-speaking male in his twenties with flu-like symptoms makes an appointment at a neighborhood health center to discuss upper respiratory symptoms and extreme fatigue. On arrival to his appointment, the nursing assistant (CNA) takes his weight, height, temperature and blood pressure, and asks him his current occupation and industry. The patient asks why the CNA needs to know his occupation. The CNA tells him that some jobs can affect people’s health, and that information about occupation helps the health center take care of him. The patient tells her that he is a house painter for a local construction company. The CNA enters all the information into the center’s electronic health record (EHR). A nurse practitioner (NP) enters the exam room, greets the patient, notes the information on the intake entry screen, and asks him some questions about his symptoms. She informs him that that he likely has a viral upper respiratory infection.

The NP reviews the patient’s record to make sure he is up to date on other healthcare needs; she sees construction in the Industry field and painter in the Occupation field. The health center providers have recently attended a training session about occupational lead poisoning. The medical director sent a follow-up email to remind the medical staff about blood lead testing, and to reiterate one of the points made in the training: that Portuguese-speaking workers have a higher risk of lead poisoning than other workers in the area. The NP confirms that he works as a painter and asks him if he has had a blood lead test since working as a painter. After he reports no previous lead testing, she orders a blood lead test. The test results show that the patient’s blood lead is elevated. The clinic staff refers the patient to an occupational health physician, who performs the appropriate evaluation and provides treatment and education to help the worker reduce exposure and prevent long-term complications of lead exposure.

A worker goes to her primary care clinic for follow-up of her type II diabetes. Despite taking her medication correctly, her diabetes is poorly controlled, with a hemoglobin A1C of 9.5. She had previously provided information on her work as a medical assistant at a local hospital working the night shift. This information, including fields for current employment status, industry, occupation, and work schedule was recorded into the electronic health record (EHR). When the nursing staff enters the reason for the clinic visit into the EHR field for chief complaint, this information triggers a pop up box that states that shift work can affect diabetes control and provides recommendations on diabetes management among shift workers. This clinical decision support tool allows the providers to adjust the patient’s medication and provide educational resources to improve the patient’s health.