This case study discusses hospital readmissions and provides healthcare professionals with recommended medical algorithms in the form of scores, models, and calculators that can aid in reducing readmissions, especially when related to antibiotic resistant microbiological pathogens.  When health analytics, such as the CDC antibiotic resistance program and other algorithms are integrated into standard hospital procedures, they can help to identify risks early and are effective tools to aid in readmission prevention.

Case Study: Readmission Blues

Jim is a 70-year-old male who was recently discharged from the hospital following an admission for congestive heart failure (CHF). He has a history of type 2 diabetes mellitus (DM), coronary artery disease (CAD), chronic obstructive pulmonary disease (COPD) and chronic renal failure (CRF). His recent past history is significant for 2 exacerbations of COPD during the past six months that were treated as an outpatient with broad-spectrum antibiotics.

Four days after hospital discharge he was brought to the Emergency Department with a severe exacerbation of COPD with hypoxemia and cyanosis. He was admitted and started on IV antibiotics. He failed to improve and his respiratory function deteriorated. He was admitted to the ICU and required mechanical ventilation. Sputum and blood culture showed Klebsiella pneumoniae resistant to multiple antibiotics. Fortunately there was an antibiotic to which the organism was still susceptible and antibiotic therapy was changed. The patient was placed in isolation to reduce spread of the organism.

Reasons for Readmission

Hospital readmissions occur for many reasons, many of which are unrelated to the reason for the previous admission. Many patients have multiple comorbid conditions, any one of which may get worse. In addition, a patient may be exposed to microbiological pathogens that can cause a nosocomial infection. Unfortunately the pathogens in hospitals have an increased risk for being antibiotic-resistant.

This patient is high risk for a nosocomial infection with an antibiotic-resistant organism. The patient has a history of previous exposures to antibiotics. He also had congestive heart failure, which can result in pulmonary edema. His diabetes may impair host responses.

Need for Vigilance With Patients

Hospitals need to be constantly vigilant in order to detect and control organisms that are resistant to antibiotics. This may include surveillance of certain patients or certain events, such as:

  1. A patient being admitted to the hospital or ICU
  2. A patient with multiple risk factors for nosocomial infection
  3. A patient undergoing a high-risk procedure
  4. A patient who is being readmitted
  5. A patient with a history of being infected with a resistant organism

Responding to Antibiotic Resistant Organisms

A number of steps can be taken to reduce the risk of nosocomial infection with antibiotic-resistant organisms. A patient with an antibiotic resistant organism should be placed in isolation. One argument for more outpatient therapy is to reduce exposure to resistant organisms within hospitals. Perhaps more important is the rational use of antibiotics through antibiotic stewardship. Avoiding inappropriate or unnecessary antibiotic therapy can reduce some of the pressure on organisms to become resistant.

Failure is Not an Option

We should be terrified about the emergence of resistance in microbiological pathogens. We have become complacent about the risks, forgetting the horrors of the days before antibiotics. Pathogens like tuberculosis and gonorrhea that were once easy to treat may some day be untreatable, with dire consequences for public health.

Use of medical algorithms geared toward early identification of risks for antibiotic resistant organisms that result in readmission is an effective strategy for hospitals to adopt. Implementation of standard procedures that incorporate the use of medical algorithms will result in better outcomes for patients and healthcare providers and this is especially true when the aiming to reduce readmissions.