This case study illustrates how medical algorithms can be successfully integrated into the clinical decision making process to achieve quicker and more accurate results.
Upon waking on Tuesday morning, Bob Jones knew something was wrong. He was seeing double and felt dizzy. He noticed that his eyelids were drooping. His stomach hurt as well, and he developed diarrhea. When he called his family doctor to figure out what was going on, he noticed it was difficult to speak clearly. His doctor directed him to go to the local Emergency Room (ER).
In the ER’s waiting room, Bob noted several familiar faces, most of whom were from his church.
The ER doctor said that several people were presenting with similar symptoms and he suspected food poisoning. He asked where Bob had eaten recently. Bob ate a few meals outside his home during the past few days:
- Potluck dinner at church
- Dinner at the local veterans hall
- Dinner at a new Mexican restaurant
Several other people in the ER had mentioned eating at the church potluck. Bob could only remember eating vegetable soup and chili at the church dinner.
Correlating Various Foods with Possible Causes of Food Poisoning
Differential Diagnosis of Foodborne Illness Based on Time of Onset and Key Symptoms
Clinical Features of Staphylococcal Food Poisoning
Clinical Features of the Long-Incubation (Diarrheal) Type of Bacillus Cereus Food Poisoning
The doctor asked if anyone had leftovers from the church meal. Bob had some vegetable soup in his refrigerator at home, which his wife brought to the hospital. The ER doctor sent a sample of the soup for testing.
In the meantime, the doctor ordered IV fluids and anti-nausea medication. He performed a thorough physical exam. Bob’s neurological exam was remarkable for bilateral nystagmus, ptosis, sluggishly reactive pupils, and a hoarse voice. Strength and sensory testing was within normal limits. The doctor was concerned about the possibility of a foodborne illness outbreak of botulism.
Risk Factors for Foodborne Botulism
Clinical Findings in Foodborne Botulism
The physician ordered spirometry and Bob was monitored with pulse oximetry and frequent vitals. An arterial blood gas was taken.
Clinical Prediction Rule for Respiratory Failure in a Patient with Foodborne Botulism
Foodborne botulism is a potentially lethal condition often caused by dangerous bacteria that grow in improperly canned foods. Due to the rarity of the illness, the hospital did not carry the antitoxin in the pharmacy. The doctor contacted the State Health Department and asked for assistance. The State Health Department agreed that Bob, as well as the others presenting with similar symptoms in the ER, were at risk for botulism and needed urgent attention to prevent potential respiratory failure and death.
Clinical Prediction Rule for Predicting Mortality Risk in Foodborne Botulism Based on Signs and Symptoms
The botulism antitoxin was rushed to the hospital. Bob was moved to an inpatient room and treatment was started.
The State Health Department contacted area hospitals to see if any other patients presented with similar symptoms. They also sent representatives to ask Bob and the other patients for the contact information of everyone who ate at the church potluck that day. Bob’s sister, who attended the potluck as well, had left for a business trip the day before. The Health Department contacted her and recommended she see a physician immediately if she developed symptoms. The Department also informed the church about the outbreak and educated members about the symptoms of foodborne illness and how to prevent them in the future.
Differential Diagnosis of Foodborne Illness Starting Within 6 Hours of Ingestion
Clinical Features of the Short-Incubation (Emetic) Type of Bacillus Cereus Food Poisoning
A few days later, the food sample returned positive for Clostridium Botulinum and the diagnosis of foodborne botulism was confirmed. Bob slowly improved with treatment over the next few weeks and was discharged from the hospital.
- While foodborne botulism may be rare, foodborne illness and gastroenteritis is quite common. A powerful algorithm can rapidly help physicians identify both common and uncommon pathogens.
- Medical algorithms, if used strategically and appropriately, can be instrumental in diagnosis, assessment and disease management.
The medical algorithms highlighted in this case study are available at The Medical Algorithms Company and also on apervita.net.
About the Authors
Umang Jain is the Health Innovations Fellow at Apervita. He is passionate about medicine, research, and business. He is a fourth year medical student at Northwestern University’s Feinberg School of Medicine and will pursue Emergency Medicine residency. Umang’s scholarly interests include surgical outcomes research, in which he is published in the fields of ENT, orthopedic, plastic, cardiac, and urologic surgery. He has also participated in research in neurodegenerative disease at MIT and Boston University. Umang’s business experience stems from his work at the Institute of Healthcare Improvement (IHI) in Boston, MA. He worked closely with Dr. Donald Berwick, Administrator of Medicare and Medicaid Services (CMS) and Sir Nigel Crisp, the former Chief Executive of UK’s National Health Service, on engaging in evidence-based healthcare improvement interventions on a global scale. Umang was also an intern at Senticare Inc. and Personica, where he evaluated EHRs and in-home health monitoring equipment.
Dr. Chad Rudnick, MD, FAAP is a board-certified pediatrician in Boca Raton, FL. He is the Medical Director of The Medical Algorithms Company. A proponent of incorporating medical technology into his practice, Dr. Rudnick uses telemedicine and medical algorithms from The Medical Algorithms Company in his daily practice to better serve his patients and their families. An accomplished medical writer, he maintains a popular pediatric blog, All Things Pediatric, and has written for numerous online and print publications including KevinMD.com.
John Svirbely, MD is a founder and Chief Medical Officer of The Medical Algorithms Company and the primary author of its medical algorithms. John is a co-founder of the Medical Algorithms Project and has developed its medical content for nearly 20 years. He has a BA degree from the Johns Hopkins University and his MD from the University of Maryland. He is a board-certified pathologist with a fellowship in medical microbiology and biomedical computing at Ohio State University. Currently he is in private practice in Cincinnati, Ohio. He has authored multiple books and articles on medical algorithms.