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When a primary care physician refers a patient with chronic kidney disease, two clocks start. The clinical one is well known: kidney disease is easier to manage the earlier a nephrologist is involved. The operational one gets less attention. It runs from the moment the referral arrives at the nephrology practice to the moment the patient sits down for the first visit, and most of it is spent inside the practice.
This post is about that second clock: where referrals wait, what the research says about referrals that never turn into visits, and what a practice can measure this month.
Why the time after referral matters in kidney care
Many patients who should see a nephrologist never do, or see one late.
- Under-referral is common. In a primary care population studied in BMC Nephrology (2017), only 21.4% of CKD patients who met at least one guideline criterion for referral were seen by a nephrologist. Following the guideline fully would have raised new-referral volume by 67.3%.
- High-risk patients are missed too. A claims study in JAMA Network Open (2022) found that nearly half of patients at high risk of kidney failure did not visit a nephrologist within a year.
- Late care shows up as unplanned dialysis. An American Institutes for Research brief (2025) estimated that about one in three Medicare fee-for-service beneficiaries who needed maintenance dialysis “crashed” into it during 2018 to 2022. In one large accountable care organization, 40% of patients with an unplanned start had no nephrology care in the prior 12 months, and their 12-month cost of care averaged $95,036 versus $25,671 for planned starts (ASN Kidney Week abstract, 2021).
Payment models now reward getting this right. Under the CMS Kidney Care Choices model, participants increased Optimal ESRD Starts, meaning planned starts of kidney replacement therapy, by 31% and preemptive transplant waitlisting by 37% in 2023, according to the CMS Innovation Center’s evaluation (2026). The model now runs through 2027 (CMS, 2026).
None of this is solved by a faster intake desk alone. But a referral that has already been sent is the easiest patient to lose and the cheapest to keep.
When PCPs refer, briefly
Referral criteria come from the KDIGO 2024 guideline for the evaluation and management of CKD, which covers thresholds for kidney function, albuminuria, rapid decline and other indications. Those decisions belong to clinicians. The rest of this post starts after the decision is made, when the referral leaves the PCP’s office.
The five places a referral waits
Between the PCP’s fax and the first visit, a referral passes through five steps. Each can add days.
- Transmission. The referral has to arrive and be recognized as a referral. Many still come by fax, mixed in with lab results, records requests and pharmacy messages.
- Intake. Someone has to read it, enter the patient, check insurance and decide what is missing. When the person who does this is also answering phones, intake waits for a quiet moment.
- Missing records. Referrals often arrive without what the nephrologist needs: recent creatinine and eGFR, urine albumin, visit notes, insurance details. The gap is long-standing. In a study in the Journal of General Internal Medicine (2000), 68% of specialists reported receiving no information from the PCP before specific referral visits.
- Reaching the patient. The patient has to be called and scheduled. Wrong numbers, numbers that no longer connect, voicemail, and patients who do not answer unknown callers turn one call into several attempts over several days.
- The first open slot. Even after the patient is reached, the next new-patient appointment may be weeks away.
Job postings show how much of this lands on one desk. A 2026 posting for a nephrology Referral/Communications Specialist at Indiana University Health lists the key responsibilities as “Answering the phones, Scheduling appointments, Faxing, Referral management”.
Referrals that never become visits
The worst outcome is not a slow referral but a lost one. There is little nephrology-specific data on this, so the best evidence comes from multi-specialty studies.
A 2018 analysis in the Journal of General Internal Medicine looked at 103,737 referral scheduling attempts from a large primary care network to 20 specialties. Only 34.8% ended in a documented completed appointment, and 38.9% never had an appointment date recorded. The authors pointed to low scheduling rates, differences between clinics, and longer wait times and distances as the drivers.
The same pattern holds for later steps in kidney care. Among dialysis patients in the Southeastern US, a study by Patzer and colleagues found that only 48.3% of patients referred for a kidney transplant started the evaluation within six months of referral (American Journal of Transplantation, 2020). A referral that has been sent is not the same as care that has started.
The referral-to-first-visit scorecard: five numbers to measure
Most practices sense that referrals take too long but cannot say where the time goes. These five numbers answer that, and most can be pulled from the fax log, the EHR and the phone system.
| Number | What it shows |
|---|---|
| Days from referral received to first review | How long referrals sit before anyone reads them |
| Share of referrals missing records | How often intake stalls on the referring office |
| Attempts to reach the patient | Whether contact information and call timing are the problem |
| Days from referral received to first visit scheduled | The total intake delay |
| Share of referrals that reach a scheduled first visit | How many referrals are lost |
Track them weekly for a month before changing anything. The slowest step is usually not the one the team would have guessed.
What can be automated, and what stays with people
Most of the work between a referral arriving and the first visit is repetitive: reading the document, entering the patient, requesting records, chasing a working phone number, calling the patient and finding a slot. That makes it a good candidate for automation. An AI referral agent can be designed to handle the routine path end to end:
- read each incoming referral and pull out the patient, the reason and the attached records;
- request missing records from the referring office with standard templates, and follow up on a set schedule;
- correct a missing or non-connecting phone number before the patient is called;
- hand the patient to a scheduling agent that calls and schedules the first visit within the practice’s rules;
- record the referral status, records and appointment in the practice’s systems, and tell the referring office where things stand.
Clinical judgment stays with people. Deciding whether a referral is urgent, whether it is appropriate, and who should be seen first is the work of nephrologists and their teams. A well-designed system gives staff a task only when a referral needs one of those decisions, and shows everything else it did so the team can check it.
At EigenH AI, this is the workflow of the Referrer, which hands patients to the Scheduler and is available through early access.
Whatever tools a practice uses, the vendor will handle protected health information, so it needs a business associate agreement. For EigenH AI: we are HIPAA compliant, independently assessed by a third party; we sign a BAA with every practice; SOC 2 is in progress.
The short version
Early referral only helps if it turns into an early visit. The time between the two is mostly spent inside the practice: in the fax tray, waiting on records, and on the phone trying to reach the patient. Measure those steps for a month, fix the slowest one, and fewer of the patients your referring physicians send you will be lost on the way in.
If you want help pulling those numbers for your practice, book a referral-to-first-visit review. For the revenue side of the same problem, see what a missed call costs a nephrology practice.
Sources
- BMC Nephrology (2017). Singh K, Waikar SS, Samal L. Evaluating the feasibility of the KDIGO CKD referral recommendations. https://link.springer.com/article/10.1186/s12882-017-0646-y
- JAMA Network Open (2022). Analysis of Specialty Nephrology Care Among Patients With Chronic Kidney Disease and High Risk of Disease Progression. https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2795414
- American Institutes for Research (2025). Crash Dialysis Trends Show Potential Areas for Medicare Quality and Cost Improvement. https://air.org/sites/default/files/2025-01/Crash-Dialysis-Trends-Research-Brief-January-2025.pdf
- American Society of Nephrology, Kidney Week (2021). CKD Healthcare Utilization Preceding Unplanned Dialysis in a Large Accountable Care Organization. https://www.asn-online.org/education/kidneyweek/2021/program-abstract.aspx?controlId=3595373
- CMS Innovation Center (2026). Kidney Care Choices (KCC) Model: Findings at a Glance. https://www.cms.gov/priorities/innovation/data-and-reports/2026/kcc-2nd-annual-report-aag
- CMS (2026). Kidney Care Choices Model Performance Year 2026 Model Update: Quick Reference. https://www.cms.gov/kidney-care-choices-model-performance-year-2026-model-update-quick-reference
- KDIGO (2024). Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease. https://kdigo.org/guidelines/ckd-evaluation-and-management/
- Journal of General Internal Medicine (2000). Gandhi TK, et al. Communication breakdown in the outpatient referral process. https://pubmed.ncbi.nlm.nih.gov/11029676/
- Indiana University Health (2026). Referral/Communications Specialist, Nephrology (job posting). https://olthjobs.com/europe/referral-communications-specialist-nephrology-full-time-days-indiana-university-health/
- Journal of General Internal Medicine (2018). Closing the Referral Loop: an Analysis of Primary Care Referrals to Specialists in a Large Health System. https://pmc.ncbi.nlm.nih.gov/articles/PMC5910374/
- American Journal of Transplantation (2020). Patzer RE, et al. Dialysis facility referral and start of evaluation for kidney transplantation among patients treated with dialysis in the Southeastern United States. https://pmc.ncbi.nlm.nih.gov/articles/PMC10204587/