While being discharged from the hospital even after a minor procedure is not simple (due to regulatory documentation requirements often hard for both patients and physicians to sift through), the process for a patient with co-morbidities after a prolonged stay is daunting. There are physicians from multiple specialties, various non-physician providers, social worker, and the case manager, all of whom address different discharge-related issues. It is frustrating for both a provider and patient to experience the “I really can’t answer that question” moment. Lack of effective interdisciplinary communication may lead to medical errors, and either premature or delayed discharges. The date of discharge is estimated soon after admission. Some hospitals have a focus on the clock when planning discharges. If planning occurs too early, it does not account for changes in patient needs and wrong instructions might be given. Transportation and home aid needs are time-sensitive. In contrast, some planning needs to be considered early in the admission when discharge to a non-acute care facility is obvious due to the diagnosis and/or social situation of the patient. One recent study in JAMA from the Brigham and Women’s Hospital identified seven clinical factors predicting hospital readmission: a hemoglobin less than 12 g/dL on discharge, discharge from an oncology service, low serum sodium level on discharge, a procedure (via ICD-9 standards) during admission, non-elective admission, length of stay > 4 days, and number of admissions during the previous year. Another study examined many predictive models found in the literature. “Of 7843 citations reviewed, 30 studies of 26 unique models met the inclusion criteria. The most common outcome used was 30-day readmission; only 1 model specifically addressed preventable readmissions. Fourteen models that relied on retrospective administrative data could be potentially used to risk-adjust readmission rates for hospital comparison; of these, 9 were tested in large US populations and had poor discriminative ability…Seven models could potentially be used to identify high-risk patients for intervention early during a hospitalization …, and 5 could be used at hospital discharge…” The study’s conclusion was that most prediction models perform poorly or require improvement. Perhaps one reason for this result lies in the fact that these models traditionally either fall into a clinical or administrative model. I believe that better success might be achieved if administrative and clinical predictive models are combined. Better analytics programs applied real-time in the EHR will facilitate integration of these perspectives.
The topic of transitional care has received attention because a poor discharge process results in higher readmission rates, a new benchmark focus of Medicare. Hospitals might be very good at meeting regulatory requirements but the patient’s understanding of diagnoses and instructions (both care and follow-up) is often not clear. Though required via regulations, the caregiver may not even be included in the process. I will discuss areas which can benefit from technology. Some of the technology mentioned below might not necessarily be available in the context described but feasible.
- Durable equipment needs: The care coordinator is generally the point person regarding the patient’s durable equipment needs upon discharge. Ordering the equipment (specifications and date, time, and place of delivery) might be the job of someone else (therapist, physician). Digital tools can expedite equipment procurement. Analytics from the EHR (mining diagnoses, equipment in use at the end of the hospitalization, expected place of transition, etc) might determine the individual’s ambulation, oxygen, bed, or other equipment requirements. This can act as a preliminary checklist from which the coordinator can start, rather than personally going through the EHR or surveying providers. A digital ordering program can directly interact with the distributor to check product availability and verify delivery. Another useful tool would aggregate equipment distributors which are stratified according to certification (Medicare bidding approval status), cheapest price, and best rated service (by patients and/or institutions).
- Visiting nurses: Often the home needs assessment for visiting nurses is done once the patient is discharged. This can be expedited with the help of a caregiver with the assessment completed in the hospital. Consider a tool into which the physician’s orders or recommendations for home nursing are placed and shared with the visiting nurse entity, the patient, and the caregiver. It would include the nursing assessment, and a video of the home environment (a factor in the assessment itself). This would obviate the need for a dedicated assessment visit. Visiting nurses themselves should be equipped with mobile technology which would: document their time schedule for billing, interventions, record and transmit vital signs (measured via digital remote monitors), orders, and contain a digital messaging program.
- Scheduling of outpatient provider appointments: Although there is some evidence that in a general medical population early follow-up appointments do not impact readmission rates(notwithstanding a slightly higher emergency department visit and death rate), some patient including those with congestive heart failure have been shown to benefit from early follow-up. The success of a growing number of commercially available mobile apps intended to streamline scheduling of physician appointments is testimony to the need it is addressing in the non-acute setting. Patient portal use is a requirement of EHR’s Meaningful Use Stage 2. One way of encouraging patient participation in portal use would be activating it by utilizing a discharge planning scheduling application of the portal at the time of discharge. This fits into an overall strategy of point of engagement implementation of technology.
These are only a few highlights of the complexity of the discharge process. All physicians have dealt with the many questions, complications, and frustration experienced by patients after discharge. A failed process creates unnecessary work, expense and bad outcomes. Digital health technology’s image to many physicians is represented by the EHR in its present form, which is not what the doctor ordered. It is not intuitive, cumbersome, and encourages impersonal encounters with patients. I will explore in future posts how digital technologies other than the EHR will change medicine in ways that physicians will appreciate them.