Hari Shankar Meshram MD, Sanjeev Gulati MD, Sanshriti Chauhan MD, Saurabh Puri MD, Sourabh Sharma MD, Varun Kumar Bandi MD
Corresponding author: Sanjeev Gulati
Contact Information: Sgulati2002@gmail.com
DOI: 10.12746/swjm.v14i59.1615
Introduction: Telenephrology is an emerging but underreported area of practice. This study evaluated nephrologists’ confidence in diagnosing and managing a range of kidney conditions using telenephrology.
Methods: A cross-sectional online survey was conducted between September 2024 and January 2025 among practicing nephrologists in India. The questionnaire included 11 general and 110 condition-specific items. Respondents rated their confidence across clinical scenarios using a Likert scale. A response of moderate, high, or very high (≥60% confidence) was defined as “confident.”
Results: A total of 136 nephrologists from India participated. Of these, 73 (53.7%) used synchronous methods, with half conducting video consultations. The most frequently cited limitations were incomplete clinical examination (115; 84.6%) and medico-legal risks (89; 65.4%). Overall, 11 (44%) of 25 kidney conditions in the naïve diagnostic setting surpassed the confidence threshold. In contrast, only 2 (8%) of 25 conditions in naïve management reached this benchmark, primarily urinary tract infections and early-stage CKD (≤G3a). In chronic dialysis care, confidence was higher for hemodialysis-related complications but notably lower for peritoneal dialysis issues. Follow-up care in general nephrology (97; 71.3%) and kidney transplant recipients (103; 75.7%) exceeded the threshold in several scenarios. Counseling-related tasks reflected the lowest confidence (43; 31.6%). Factors such as pediatric exposure, academic affiliation, years of experience, sector of work, and workload did not significantly affect confidence levels.
Conclusion: This India-focused survey highlights promising confidence in telenephrology for diagnosis and follow-up but underscores the need for targeted improvements in management and counselling applications.
Keywords: Telenephrology, Nephrologists, Survey, Hemodialysis, telemedicine
The World Health Organization defines telehealth as the delivery of health care services through information and communication technologies in which patients and providers are separated by distance, and which may be used for diagnosis, treatment, research, evaluation, and continuing education.1 When applied to nephrology, telehealth is recognized as telenephrology. Over the past two decades, there has been a gradual transition from exclusively in-person visits to virtual care, a trend accelerated by the impact of the COVID-19 pandemic.
Despite this growth, there are few reports on telenephrology, particularly from the patient’s perspective, and only limited large-scale studies have explored the complexities of its implementation.2 The attitudes and practice patterns of nephrologists are also rarely reported, especially in emerging nations such as India. This knowledge gap is further compounded by the variability in nephrology centers’ policies and the acceptability of telenephrology.3 Moreover, no prior study has evaluated nephrologists’ confidence in using telenephrology for specific kidney conditions.
The objective of this study was to characterize current telenephrology practice patterns and confidence levels across a range of kidney conditions among nephrologists in India. Identifying areas of high and low confidence could inform improvements to the existing system and provide a basis for targeted interventions.
The survey was constructed by the investigators (HSM and SC). Ethical approval was obtained from the Institutional Ethics Committee (Approval No. EC/NEW/INST/2021/2140: F-442/25). A pilot version was circulated among 10 nephrologists for cross-validation. Based on their feedback, a few items requiring highly granular details of diagnosis and management were excluded to reduce fatigue and improve response rates.
The final survey was administered online using Google Forms and allowed only a single, non-editable response. It was fully anonymous, as no identifying information, such as email address, name, gender, or institution, was requested. The survey was distributed to nephrologists across India between September 2024 and January 2025 via email and phone calls, and responses were accepted until January 11, 2025.
The final questionnaire comprised 11 general questions and 110 condition-specific questions, all closed-ended. The complete list of items is provided in Supplementary Table 1. General questions included place of work, sector (public or private), pediatric exposure, years of experience, and the average number of new outpatient registrations per month (to estimate workload). Additional items assessed current practice patterns in telenephrology (not practicing, synchronous, asynchronous, remote monitoring, or mobile applications), the proportion of general and transplant patients managed using telenephrology, data storage practices, and the perceived role of telenephrology in clinical trials. The modality of practice (audio vs. video) and perceived limitations were also recorded.
Specific questions were organized into six domains: (1) naïve diagnosis, (2) naïve management, (3) counseling scenarios, (4) chronic dialysis complications, (5) follow-up of discharged general nephrology patients, and (6) follow-up of discharged kidney transplant recipients (KTRs). Confidence for each item was assessed using a 5-point Likert scale (very low, low, moderate, high, very high).
The naïve diagnosis domain (25 items) included acute kidney injury (AKI) and its common etiologies, AKI requiring dialysis, kidney biopsy, rapidly progressive glomerulonephritis, nephrotic and nephritic syndromes, autosomal dominant polycystic kidney disease (ADPKD), Alport syndrome, myeloma kidney, non-obstructive nephrolithiasis, various stages of chronic kidney disease (CKD), urinary tract infections, electrolyte disorders, and enuresis. The naïve management domain (25 items) addressed the management of these same conditions.
The counselling domain (13 items) included scenarios such as prognosis after AKI or CKD, initiation of dialysis, decisions regarding native or graft kidney biopsy, initiation of steroids or other immunosuppressive therapies (rituximab, cyclophosphamide), arteriovenous fistula creation, vaccination, reproductive counselling, and palliative care.
The chronic dialysis complications domain (18 items) included anemia, bone disease, vaccination, cardiovascular disease, pruritus, dialysis adequacy, diabetes, hypertension, volume overload, malnutrition, sexual and reproductive health, mental health issues, vascular access dysfunction, hepatitis B/C seropositivity, and HIV seropositivity. Peritoneal dialysis–specific complications (catheter dysfunction, CAPD infections, ultrafiltration failure) were also included.
The discharged-patient follow-up domain (17 items) included AKI (with or without dialysis), acute interstitial nephritis, lupus nephritis (induction/maintenance), membranous nephropathy (primary or secondary), nephrotic syndrome (conservative or immunosuppression), ANCA-associated vasculitis, and CKD with volume overload. It also covered CAPD-related complications and post-discharge follow-up of living kidney donors.
The kidney transplant follow-up domain (12 items) addressed immunosuppression tailoring (<1 year or >1 year post-transplant), augmentation of immunosuppression after infection, donor-specific antibody surveillance, BK virus monitoring, reproductive and sexual health, malignancy surveillance, cystitis/lower UTI, gastroenteritis, respiratory infections, post-transplant diabetes mellitus, and adherence to immunosuppressive drugs.
Data was reported as numbers and percentages for the Likert scale and confidence. Continuous data were reported as median (interquartile range). We did chi-square tests and logistic regression analysis. A p-value <0.05 was a measure of significance in this report. All statistical analysis was performed using SPSS version 16.
A total of 136 nephrologists from India participated, representing 19 states. The largest groups were from Delhi (33 [24%]) and Gujarat (15 [11%]). Of the respondents, 10 (7%) practiced exclusive pediatric nephrology, while 67 (49%) managed both adult and pediatric patients. Most worked in the private sector (93 [68%]). Clinical experience exceeded 10 years in 95 (70%) respondents, 16 (12%) had 5–10 years, and 4 (3%) had less than one year.
Regarding practice patterns, 28 (21%) nephrologists reported never using telenephrology. The most common modality was synchronous communication (73 [54%]), followed by asynchronous (26 [19%]) and remote patient monitoring (10 [7%]). Mobile health applications were used by 37 (27%). For most nephrologists, only 0–10% of patients were enrolled in telenephrology programs. Kidney transplant recipients (KTRs) were significantly less likely to be enrolled in follow-up via telenephrology compared to general kidney patients (55 [40%] vs. 81 [60%]; p < 0.001).
On digital record-keeping, 68 (50%) respondents did not store any digital information, while approximately one-quarter stored data, with or without patient consent. A large majority, 112 (82%), agreed that telenephrology could improve enrollment and follow-up of patients in clinical trials.
Video consultation was the dominant mode (71 [52%]), followed by phone messages (53 [39%]) and audio-only consults (48 [35%]). A formal telehealth software platform was used by 23 (17%). Commonly cited limitations included inability to perform a complete clinical exam (115 [85%]), medico-legal risks (89 [65%]), misinterpretation of clinical signs (81 [60%]), reduced patient trust (67 [49%]), lack of standardized protocols (62 [46%]), and financial barriers (42 [31%]). Patients’ lack of tech literacy was noted more frequently (36 [26%]) than physicians’ (10 [7%]). See Figure 1.
Table 1 shows naïve diagnosis and management where confidence exceeded the 60% threshold in 11 (44%) of 25 diagnostic scenarios: lower UTI (102 [75%]), ADPKD (100 [74%]), nephrolithiasis (91 [67%]), CKD G1–G3a (93 [68%]), nephrotic syndrome (89 [65%]), CKD G3b–G5ND (88 [65%]), and enuresis (82 [60%]). Contrast-induced AKI and mild-to-moderate hyperkalemia did not meet the threshold. Only two management scenarios surpassed 60% confidence: lower UTI (92 [68%]) and CKD G1–G3a (87 [64%]). Confidence was lowest for RPGN, AKI requiring biopsy, and AKI requiring dialysis.
Table 1. Confidence Scale and Percentage Confidence of Various Naïve Diagnoses and the Management Related to Kidney Health
| Naïve Diagnosis | Naïve Management | |||||||||||||||||
| Confidence Scale | p-value | % Confidence | p-value | Confidence Scale | p-value | Confidence | p-value | |||||||||||
| Kidney Health Conditions | Very Low | Low | Moderate | High | Very High | No | Yes | Very Low | Low | Moderate | High | Very High | No | Yes | ||||
| AKI KDIGO III, no KRT | 22 (16.18) | 40 (29.41) | 28 (20.59) | 34 (25) | 12 (8.82) | 0.0017 | 62 (45.59) | 74 (54.41) | 0.3035 | 32 (23.5) | 43 (31.6) | 29 (21.3) | 28 (20.6) | 4 (2.9) | <0.01 | 75 (55.1) | 61 (44.9) | 0.2299 |
| AKI KRT | 30 (22.06) | 30 (22.06) | 30 (22.06) | 30 (22.06) | 16 (11.76) | 0.2174 | 60 (44.12) | 76 (55.88) | 0.1701 | 47 (34.6) | 39 (28.7) | 26 (19.1) | 17 (12.5) | 7 (5.1) | <0.01 | 86 (63.2) | 50 (36.8) | 0.0020 |
| AKI (KDIGO I or II) Hypovolemia | 34 (25) | 42 (30.88) | 29 (21.32) | 20 (14.71) | 11 (8.09) | 0.0003 | 76 (55.88) | 60 (44.12) | 0.1701 | 32 (23.5) | 48 (35.3) | 29 (21.3) | 22 (16.2) | 5 (3.7) | 0.0019 | 80 (58.8) | 56 (41.2) | 0.0396 |
| AKI (KDIGO I or II) Drug induced | 24 (17.65) | 40 (29.41) | 32 (23.53) | 36 (26.47) | 4 (2.94) | <0.01 | 64 (47.06) | 72 (52.94) | 0.4927 | 25 (18.4) | 39 (28.7) | 36 (26.5) | 30 (22.1) | 6 (4.4) | <0.01 | 64 (47.1) | 72 (52.9) | 0.4927 |
| AKI (KDIGO I or II) Infection | 21 (15.44) | 43 (31.62) | 43 (31.62) | 26 (19.12) | 3 (2.21) | <0.01 | 64 (47.06) | 72 (52.94) | 0.4927 | 27 (19.9) | 43 (31.6) | 36 (26.5) | 24 (17.6) | 6 (4.4) | <0.01 | 70 (51.5) | 66 (48.5) | 0.7316 |
| AKI (KDIGO I or II) Cardio-renal | 30 (22.06) | 47 (34.56) | 37 (27.21) | 18 (13.24) | 4 (2.94) | <0.01 | 77 (56.62) | 59 (43.38) | 0.1227 | 29 (21.3) | 45 (33.1) | 40 (29.4) | 17 (12.5) | 5 (3.7) | 0.0132 | 74 (54.4) | 62 (45.6) | 0.3035 |
| AKI (KDIGO I or II) Hepatorenal | 34 (25) | 47 (34.56) | 39 (28.68) | 13 (9.56) | 3 (2.21) | <0.01 | 81 (59.56) | 55 (40.44) | 0.0258 | 33 (24.3) | 45 (33.1) | 40 (29.4) | 12 (8.8) | 6 (4.4) | 0.1147 | 78 (57.4) | 58 (42.6) | 0.0863 |
| AKI (KDIGO I or II) Contrast induced | 18 (13.24) | 34 (25) | 38 (27.94) | 42 (30.88) | 4 (2.94) | <0.01 | 52 (38.24) | 84 (61.76) | 0.0061 | 28 (20.6) | 38 (27.9) | 36 (26.5) | 28 (20.6) | 6 (4.4) | <0.01 | 66 (48.5) | 70 (51.5) | 0.7316 |
| AKI (KDIGO I or II) Obstruction | 22 (16.18) | 37 (27.21) | 32 (23.53) | 43 (31.62) | 2 (1.47) | <0.01 | 59 (43.38) | 77 (56.62) | 0.1227 | 31 (22.8) | 39 (28.7) | 35 (25.7) | 23 (16.9) | 8 (5.9) | <0.01 | 70 (51.5) | 66 (48.5) | 0.7316 |
| AKI requiring biopsy | 34 (25) | 41 (30.15) | 33 (24.26) | 26 (19.12) | 2 (1.47) | <0.01 | 75 (55.15) | 61 (44.85) | 0.2299 | 50 (36.8) | 41 (30.1) | 27 (19.9) | 13 (9.6) | 5 (3.7) | 0.0031 | 91 (66.9) | 45 (33.1) | 0.0001 |
| RPGN | 39 (28.68) | 28 (20.59) | 29 (21.32) | 32 (23.53) | 8 (5.88) | 0.0006 | 67 (49.26) | 69 (50.74) | 0.8638 | 46 (33.8) | 47 (34.6) | 20 (14.7) | 18 (13.2) | 5 (3.7) | <0.01 | 93 (68.4) | 43 (31.6) | <0.01 |
| Nephrotic syndrome | 15 (11.03) | 32 (23.53) | 29 (21.32) | 44 (32.35) | 16 (11.76) | 0.0003 | 47 (34.56) | 89 (65.44) | 0.0003 | 30 (22.1) | 41 (30.1) | 24 (17.6) | 32 (23.5) | 9 (6.6) | <0.01 | 71 (52.2) | 65 (47.8) | 0.6069 |
| Nephritic syndrome | 24 (17.65) | 37 (27.21) | 31 (22.79) | 35 (25.74) | 9 (6.62) | 0.0008 | 61 (44.85) | 75 (55.15) | 0.2299 | 31 (22.8) | 49 (36.0) | 25 (18.4) | 24 (17.6) | 7 (5.1) | <0.01 | 80 (58.8) | 56 (41.2) | 0.0396 |
| ADPKD spectrum | 14 (10.29) | 22 (16.18) | 35 (25.74) | 58 (42.65) | 7 (5.15) | <0.01 | 36 (26.47) | 100 (73.53) | <0.01 | 18 (13.2) | 38 (27.9) | 29 (21.3) | 39 (28.7) | 12 (8.8) | <0.01 | 56 (41.2) | 80 (58.8) | 0.0396 |
| Alport syndrome | 28 (20.59) | 30 (22.06) | 40 (29.41) | 33 (24.26) | 5 (3.68) | <0.01 | 58 (42.65) | 78 (57.35) | 0.0863 | 25 (18.4) | 44 (32.4) | 37 (27.2) | 23 (16.9) | 7 (5.1) | <0.01 | 69 (50.7) | 67 (49.3) | 0.8638 |
| Myeloma kidney | 31 (22.79) | 30 (22.06) | 40 (29.41) | 30 (22.06) | 5 (3.68) | <0.01 | 61 (44.85) | 75 (55.15) | 0.2299 | 34 (25.0) | 42 (30.9) | 33 (24.3) | 21 (15.4) | 6 (4.4) | <0.01 | 76 (55.9) | 60 (44.1) | 0.1701 |
| Nephrolithiasis (non-obstructive stones) | 12 (8.82) | 33 (24.26) | 36 (26.47) | 51 (37.5) | 4 (2.94) | <0.01 | 45 (33.09) | 91 (66.91) | 0.0001 | 19 (14.0) | 38 (27.9) | 42 (30.9) | 29 (21.3) | 8 (5.9) | <0.01 | 57 (41.9) | 79 (58.1) | 0.0592 |
| CKD KDIGO G1–G3a | 17 (12.5) | 26 (19.12) | 30 (22.06) | 53 (38.97) | 10 (7.35) | <0.01 | 43 (31.62) | 93 (68.38) | 0.0000 | 17 (12.5) | 32 (23.5) | 35 (25.7) | 40 (29.4) | 12 (8.8) | <0.01 | 49 (36.0) | 87 (64.0) | 0.0011 |
| CKD KDIGO G3b–G5ND | 22 (16.18) | 26 (19.12) | 27 (19.85) | 54 (39.71) | 7 (5.15) | <0.01 | 48 (35.29) | 88 (64.71) | 0.0006 | 25 (18.4) | 37 (27.2) | 31 (22.8) | 33 (24.3) | 10 (7.4) | <0.01 | 62 (45.6) | 74 (54.4) | 0.3035 |
| CKD dialysis initiation | 36 (26.47) | 25 (18.38) | 37 (27.21) | 34 (25) | 4 (2.94) | <0.01 | 61 (44.85) | 75 (55.15) | 0.2299 | 37 (27.2) | 37 (27.2) | 30 (22.1) | 25 (18.4) | 7 (5.1) | <0.01 | 74 (54.4) | 62 (45.6) | 0.3035 |
| Lower UTI | 11 (8.09) | 23 (16.91) | 41 (30.15) | 53 (38.97) | 7 (5.15) | <0.01 | 34 (25) | 102 (75) | <0.01 | 16 (11.8) | 28 (20.6) | 36 (26.5) | 44 (32.4) | 12 (8.8) | <0.01 | 44 (32.4) | 92 (67.6) | 0.0000 |
| Pyelonephritis | 26 (19.12) | 30 (22.06) | 36 (26.47) | 33 (24.26) | 11 (8.09) | 0.0071 | 56 (41.18) | 80 (58.82) | 0.0396 | 29 (21.3) | 37 (27.2) | 34 (25.0) | 31 (22.8) | 5 (3.7) | <0.01 | 66 (48.5) | 70 (51.5) | 0.7316 |
| Hyponatremia (mild/moderate) | 35 (25.74) | 24 (17.65) | 39 (28.68) | 36 (26.47) | 2 (1.47) | <0.01 | 59 (43.38) | 77 (56.62) | 0.1227 | 35 (25.7) | 38 (27.9) | 31 (22.8) | 26 (19.1) | 6 (4.4) | <0.01 | 73 (53.7) | 63 (46.3) | 0.3912 |
| Hyperkalemia (mild/moderate) | 30 (22.06) | 27 (19.85) | 29 (21.32) | 46 (33.82) | 4 (2.94) | <0.01 | 57 (41.91) | 79 (58.09) | 0.0592 | 37 (27.2) | 37 (27.2) | 25 (18.4) | 31 (22.8) | 6 (4.4) | <0.01 | 74 (54.4) | 62 (45.6) | 0.3035 |
| Enuresis | 21 (15.44) | 33 (24.26) | 54 (39.71) | 27 (19.85) | 1 (0.74) | <0.01 | 54 (39.71) | 82 (60.29) | 0.0164 | 27 (19.9) | 42 (30.9) | 35 (25.7) | 24 (17.6) | 8 (5.9) | <0.01 | 69 (50.7) | 67 (49.3) | 0.8638 |
Abbreviations: AKI: acute kidney injury; KDIGO: kidney disease initiative and global outcome; RPGN: rapid progressive glomerulonephritis; CKD: chronic kidney disease; KRT: kidney replacement therapy; UTI: urinary tract infection; ADPKD: autosomal dominant polycystic kidney disease. Credit of questions: Meshram HS et al(Current author). The p-value for both likert scale of confidence and binary (yes/no) confidence threshold reaching cut-off 60% was calculated by chi square test.
Figure 2 illustrates the confidence gap: mean diagnostic confidence exceeded management across all 26 scenarios (mean difference 0.18; 95% CI 0.12–0.24; p < 0.001). Notable gaps occurred in ADPKD (Δ0.31; 95% CI 0.22–0.40; p < 0.001) and lower UTI (Δ0.25; 95% CI 0.16–0.34; p < 0.001); smaller, nonsignificant gaps appeared for AKI requiring dialysis (Δ0.02; 95% CI −0.05–0.09; p = 0.58) and RPGN (Δ0.03; 95% CI −0.04–0.10; p = 0.42).
Figure 2 Naïve Diagnosis vs Management Confidence.
On Subgroup analysis (Supplementary Table 2), most diagnostic confidence levels were not associated with demographic or practice variables. Exceptions included lower confidence in diagnosing hypovolemic AKI among physicians with high outpatient volumes (aOR 0.44; 95% CI 0.21–0.94; p = 0.035) and in diagnosing lower UTIs among academic nephrologists (aOR 0.30; 95% CI 0.12–0.78; p = 0.014). In management scenarios, pediatric-exposed nephrologists showed lower confidence in managing nephrotic (aOR 0.31; 95% CI 0.15–0.66; p = 0.002) and nephritic syndromes (aOR 0.34; 95% CI 0.16–0.72; p = 0.005).
Table 2 shows confidence in various kidney conditions. Confidence was above 60% for managing anemia (105 [77%]), bone disease (100 [74%]), vaccination (107 [79%]), cardiovascular disease (86 [63%]), pruritus (97 [71%]), diabetes (99 [73%]), hypertension (91 [67%]), and viral hepatitis (86 [63%]). It was below threshold for peritoneal dialysis catheter dysfunction (49 [36%]) and ultrafiltration failure (53 [39%]).
Table 2. Confidence Scale and Percentage Confidence of Various Kidney Health Conditions
| Kidney Health Conditions | Confidence Scale | p-value | Confidence | p-value | |||||
| Very Low | Low | Moderate | High | Very High | No | Yes | |||
| Counselling scenarios | |||||||||
| AKI recovery prognosis | 17 (12.5) | 38 (27.94) | 33 (24.26) | 38 (27.94) | 10 (7.35) | 0.0001 | 55 (40.44) | 81 (59.56) | 0.0258 |
| CKD stage 1 to 5 non-dialysis prognosis | 15 (11.03) | 25 (18.38) | 43 (31.62) | 45 (33.09) | 8 (5.88) | <0.001 | 40 (29.41) | 96 (70.59) | <0.001 |
| Dialysis initiation in CKD | 26 (19.12) | 29 (21.32) | 26 (19.12) | 37 (27.21) | 9 (6.62) | 0.0025 | 55 (40.44) | 81 (59.56) | 0.0258 |
| Kidney biopsy (native) | 29 (21.32) | 35 (25.74) | 29 (21.32) | 37 (27.21) | 6 (4.41) | 0.0002 | 64 (47.06) | 72 (52.94) | 0.4927 |
| Kidney biopsy (graft) | 34 (25) | 39 (28.68) | 32 (23.53) | 34 (25) | 6 (4.41) | 0.0001 | 73 (53.68) | 63 (46.32) | 0.3912 |
| Starting of steroids | 27 (19.85) | 36 (26.47) | 34 (25) | 32 (23.53) | 7 (5.15) | 0.0004 | 63 (46.32) | 73 (53.68) | 0.3912 |
| Starting rituximab | 41 (30.15) | 34 (25) | 27 (19.85) | 24 (17.65) | 10 (7.35) | 0.0005 | 75 (55.15) | 61 (44.85) | 0.2299 |
| Starting cyclophosphamide | 46 (33.82) | 34 (25) | 25 (18.38) | 25 (18.38) | 6 (4.41) | <0.001 | 80 (58.82) | 56 (41.18) | 0.0396 |
| Starting other immunosuppression | 46 (33.82) | 33 (24.26) | 29 (21.32) | 27 (19.85) | 9 (6.62) | 0.0001 | 79 (58.09) | 57 (41.91) | 0.0592 |
| AVF | 24 (17.65) | 39 (28.68) | 35 (25.74) | 36 (26.47) | 2 (1.47) | <0.001 | 63 (46.32) | 73 (53.68) | 0.3912 |
| Vaccination | 16 (11.76) | 21 (15.44) | 41 (30.15) | 51 (37.5) | 7 (5.15) | <0.001 | 37 (27.21) | 99 (72.79) | <0.001 |
| Reproduction & contraception | 16 (11.76) | 23 (16.91) | 44 (32.35) | 34 (25) | 19 (13.97) | 0.0005 | 39 (28.68) | 97 (71.32) | <0.001 |
| Palliative care | 23 (16.91) | 30 (22.06) | 38 (27.94) | 37 (27.21) | 8 (5.88) | 0.0002 | 53 (38.97) | 83 (61.03) | 0.0101 |
| Dialysis unit follow-up | |||||||||
| CKD – Anemia | 12 (8.8) | 19 (14.0) | 31 (22.8) | 57 (41.9) | 17 (12.5) | <0.001 | 31 (22.8) | 105 (77.2) | <0.001 |
| CKD – MBD | 11 (8.1) | 25 (18.4) | 29 (21.3) | 54 (39.7) | 17 (12.5) | <0.001 | 36 (26.5) | 100 (73.5) | <0.001 |
| CKD – Vaccination | 8 (5.9) | 21 (15.4) | 20 (14.7) | 66 (48.5) | 21 (15.4) | <0.001 | 29 (21.3) | 107 (78.7) | <0.001 |
| CKD – Cardiovascular disease | 18 (13.2) | 32 (23.5) | 37 (27.2) | 40 (29.4) | 9 (6.6) | <0.001 | 50 (36.8) | 86 (63.2) | 0.0020 |
| CKD – Pruritus | 10 (7.4) | 29 (21.3) | 30 (22.1) | 51 (37.5) | 16 (11.8) | <0.001 | 39 (28.7) | 97 (71.3) | <0.001 |
| CKD – Dialysis inadequacy | 17 (12.5) | 43 (31.6) | 34 (25.0) | 32 (23.5) | 10 (7.4) | <0.001 | 60 (44.1) | 76 (55.9) | 0.1701 |
| CKD – Diabetes | 11 (8.1) | 26 (19.1) | 34 (25.0) | 51 (37.5) | 14 (10.3) | <0.001 | 37 (27.2) | 99 (72.8) | <0.001 |
| CKD – Hypertension | 12 (8.8) | 33 (24.3) | 25 (18.4) | 52 (38.2) | 14 (10.3) | <0.001 | 45 (33.1) | 91 (66.9) | 0.0001 |
| CKD – Volume overload | 21 (15.4) | 43 (31.6) | 34 (25.0) | 31 (22.8) | 7 (5.1) | <0.001 | 64 (47.1) | 72 (52.9) | 0.4927 |
| CKD – Malnutrition | 14 (10.3) | 47 (34.6) | 32 (23.5) | 32 (23.5) | 11 (8.1) | <0.001 | 61 (44.9) | 75 (55.1) | 0.2299 |
| CKD – Sexual & reproductive issues | 16 (11.8) | 41 (30.1) | 37 (27.2) | 30 (22.1) | 12 (8.8) | 0.0001 | 57 (41.9) | 79 (58.1) | 0.0592 |
| CKD – Mental health issues | 22 (16.2) | 50 (36.8) | 32 (23.5) | 23 (16.9) | 9 (6.6) | <0.001 | 72 (52.9) | 64 (47.1) | 0.4927 |
| CKD – Vascular access dysfunction | 24 (17.6) | 43 (31.6) | 34 (25.0) | 28 (20.6) | 7 (5.1) | <0.001 | 67 (49.3) | 69 (50.7) | 0.8638 |
| CKD – Hepatitis B/C seropositivity | 13 (9.6) | 37 (27.2) | 38 (27.9) | 39 (28.7) | 9 (6.6) | <0.001 | 50 (36.8) | 86 (63.2) | 0.0020 |
| CKD – HIV seropositivity | 15 (11.0) | 47 (34.6) | 37 (27.2) | 31 (22.8) | 6 (4.4) | <0.001 | 62 (45.6) | 74 (54.4) | 0.3035 |
| PD – Catheter dysfunction | 38 (27.9) | 49 (36.0) | 27 (19.9) | 17 (12.5) | 5 (3.7) | <0.001 | 87 (64.0) | 49 (36.0) | 0.0011 |
| PD – Infection | 32 (23.5) | 44 (32.4) | 28 (20.6) | 24 (17.6) | 8 (5.9) | <0.001 | 76 (55.9) | 60 (44.1) | 0.1701 |
| PD – Ultrafiltration failure | 34 (25.0) | 49 (36.0) | 27 (19.9) | 20 (14.7) | 6 (4.4) | <0.001 | 83 (61.0) | 53 (39.0) | 0.0101 |
| General nephrology follow-up | |||||||||
| AKI no KRT | 10 (7.4) | 22 (16.2) | 36 (26.5) | 54 (39.7) | 14 (10.3) | <0.001 | 32 (23.5) | 104 (76.5) | <0.001 |
| AKI KRT | 18 (13.2) | 31 (22.8) | 45 (33.1) | 32 (23.5) | 10 (7.4) | <0.001 | 49 (36.0) | 87 (64.0) | 0.0011 |
| AIN | 10 (7.4) | 27 (19.9) | 43 (31.6) | 44 (32.4) | 12 (8.8) | <0.001 | 37 (27.2) | 99 (72.8) | <0.001 |
| Lupus nephritis – induction therapy | 21 (15.4) | 38 (27.9) | 44 (32.4) | 24 (17.6) | 9 (6.6) | <0.001 | 59 (43.4) | 77 (56.6) | 0.1227 |
| Lupus nephritis – maintenance therapy | 13 (9.6) | 30 (22.1) | 35 (25.7) | 46 (33.8) | 12 (8.8) | <0.001 | 43 (31.6) | 93 (68.4) | <0.001 |
| IgA nephropathy – conservative therapy | 6 (4.4) | 27 (19.9) | 43 (31.6) | 47 (34.6) | 13 (9.6) | <0.001 | 33 (24.3) | 103 (75.7) | <0.001 |
| IgA nephropathy – on immunosuppression | 15 (11.0) | 29 (21.3) | 44 (32.4) | 38 (27.9) | 10 (7.4) | <0.001 | 44 (32.4) | 92 (67.6) | <0.001 |
| Membranous nephropathy – conservative | 9 (6.6) | 22 (16.2) | 42 (30.9) | 47 (34.6) | 16 (11.8) | <0.001 | 31 (22.8) | 105 (77.2) | <0.001 |
| Membranous nephropathy – immunosuppression | 16 (11.8) | 26 (19.1) | 50 (36.8) | 33 (24.3) | 11 (8.1) | <0.001 | 42 (30.9) | 94 (69.1) | <0.001 |
| Nephrotic syndrome (follow-up) | 13 (9.6) | 24 (17.6) | 41 (30.1) | 43 (31.6) | 15 (11.0) | <0.001 | 37 (27.2) | 99 (72.8) | <0.001 |
| AAV induction | 27 (19.9) | 34 (25.0) | 44 (32.4) | 23 (16.9) | 8 (5.9) | <0.001 | 61 (44.9) | 75 (55.1) | 0.2299 |
| AAV maintenance | 15 (11.0) | 31 (22.8) | 47 (34.6) | 34 (25.0) | 9 (6.6) | <0.001 | 46 (33.8) | 90 (66.2) | 0.0002 |
| CKD Volume overload | 23 (16.9) | 30 (22.1) | 48 (35.3) | 28 (20.6) | 7 (5.1) | <0.001 | 53 (39.0) | 83 (61.0) | 0.0101 |
| cPD catheter dysfunction | 28 (20.6) | 43 (31.6) | 37 (27.2) | 21 (15.4) | 7 (5.1) | <0.001 | 71 (52.2) | 65 (47.8) | 0.6069 |
| cPD Infection | 26 (19.1) | 43 (31.6) | 32 (23.5) | 25 (18.4) | 10 (7.4) | 0.0003 | 69 (50.7) | 67 (49.3) | 0.8638 |
| cPD UF failure | 31 (22.8) | 42 (30.9) | 39 (28.7) | 18 (13.2) | 6 (4.4) | <0.001 | 73 (53.7) | 63 (46.3) | 0.3912 |
| Living donor nephrectomy routine follow-up | 13 (9.6) | 19 (14.0) | 44 (32.4) | 33 (24.3) | 27 (19.9) | 0.0003 | 32 (23.5) | 104 (76.5) | <0.001 |
| Kidney transplant unit follow-up | |||||||||
| Tailoring immunosuppression <1 year | 27 (19.9) | 40 (29.4) | 40 (29.4) | 21 (15.4) | 8 (5.9) | <0.001 | 67 (49.3) | 69 (50.7) | 0.8638 |
| Tailoring immunosuppression >1 year | 11 (8.1) | 29 (21.3) | 39 (28.7) | 47 (34.6) | 10 (7.4) | <0.001 | 40 (29.4) | 96 (70.6) | <0.001 |
| Augmenting immunosuppression post-infection | 25 (18.4) | 38 (27.9) | 38 (27.9) | 26 (19.1) | 9 (6.6) | 0.0003 | 63 (46.3) | 73 (53.7) | 0.3912 |
| DSA surveillance | 19 (14.0) | 31 (22.8) | 45 (33.1) | 31 (22.8) | 10 (7.4) | <0.001 | 50 (36.8) | 86 (63.2) | 0.0020 |
| BKV surveillance | 15 (11.0) | 27 (19.9) | 50 (36.8) | 36 (26.5) | 8 (5.9) | <0.001 | 42 (30.9) | 94 (69.1) | <0.001 |
| Reproductive & sexual well-being | 16 (11.8) | 27 (19.9) | 49 (36.0) | 35 (25.7) | 9 (6.6) | <0.001 | 43 (31.6) | 93 (68.4) | <0.001 |
| Malignancy surveillance | 19 (14.0) | 38 (27.9) | 50 (36.8) | 21 (15.4) | 8 (5.9) | <0.001 | 57 (41.9) | 79 (58.1) | 0.0592 |
| Managing cystitis /lower UTI | 13 (9.6) | 33 (24.3) | 47 (34.6) | 35 (25.7) | 8 (5.9) | <0.001 | 46 (33.8) | 90 (66.2) | 0.0002 |
| Managing gastroenteritis | 19 (14.0) | 32 (23.5) | 45 (33.1) | 34 (25.0) | 6 (4.4) | <0.001 | 51 (37.5) | 85 (62.5) | 0.0036 |
| Managing upper respiratory tract infections | 18 (13.2) | 24 (17.6) | 44 (32.4) | 43 (31.6) | 7 (5.1) | <0.001 | 42 (30.9) | 94 (69.1) | <0.001 |
| Managing PTDM | 14 (10.3) | 28 (20.6) | 45 (33.1) | 41 (30.1) | 8 (5.9) | <0.001 | 42 (30.9) | 94 (69.1) | <0.001 |
| Medicine adherence | 17 (12.5) | 25 (18.4) | 50 (36.8) | 35 (25.7) | 9 (6.6) | <0.001 | 42 (30.9) | 94 (69.1) | <0.001 |
The p-value for both likert scale of confidence and binary (yes/no) confidence threshold reaching cut-off 60% was calculated by chi square test.
Confidence was high for immunosuppression management beyond one year (96 [71%]), but below threshold during the first year. Confidence in surveillance for BK virus (94 [69%]) and donor-specific antibodies (86 [63%]) was good; it was borderline for malignancy surveillance (79 [58%]). Confidence was high for managing post-transplant infections: UTI (90 [66%]), gastroenteritis (85 [63%]), and respiratory infections (94 [69%]), but lower for augmenting immunosuppression after infection (73 [54%]). Confidence for post-transplant diabetes and medication adherence was both 94 (69%).
Confidence was high for follow-up after AKI without dialysis (104 [77%]), AKI with dialysis (87 [64%]), acute interstitial nephritis (99 [73%]), and CKD with volume overload (72 [53%]). Glomerulonephritis follow-up was generally adequate, except for lupus nephritis and ANCA-associated vasculitis. Living donor follow-up was high (104 [77%]).
Confidence above threshold was seen in vaccination (99 [73%]), CKD prognostication (96 [71%]), reproductive counseling (97 [71%]), and palliative care (83 [61%]). Supplementary Table 3 shows that academic nephrologists had lower counseling confidence, significantly so for vaccination (aOR 0.34; 95% CI 0.14–0.87; p = 0.024) and post-discharge follow-up of nephrotic syndrome (aOR 0.36; 95% CI 0.14–0.97; p = 0.044). Private sector nephrologists were less confident than the public sector in augmenting immunosuppression post-infection (aOR 0.42; 95% CI 0.20–0.91; p = 0.027)
To the best of our knowledge, this is the first study to provide a detailed survey of telenephrology practices among nephrologists in India. The major hurdles identified were the lack of physical examination, medico-legal concerns, and financial constraints. These findings highlight the need to restructure the existing framework to incorporate uniform rules and regulations addressing both legal and financial aspects.
Although most respondents had more than five years of clinical experience, confidence levels for many kidney conditions were only moderate. The fact that experienced specialists were willing to adapt and expressed confidence in several areas indicates that a strong framework for telenephrology can be developed. Respondents reported higher confidence in making naïve diagnoses compared to naïve management, where confidence lagged significantly. Strengthening and streamlining the link between nephrologists and primary care providers at the patient’s end may help bridge this gap.
Evidence from developed countries has primarily focused on patient outcomes rather than nephrologist perspectives. A Veterans Affairs cohort study in the United States showed that patients with CKD managed through telenephrology had similar rates of CKD progression compared with those seen in person. Another U.S. study reported comparable outcomes and included nephrologist perspectives (n = 11).10 That study found nephrologists favored video consultations and were comfortable with hybrid (combined in-person and telehealth) models—similar to the pattern observed in our study. However, their study did not assess nephrologists’ confidence across individual kidney conditions. A smaller U.S. study demonstrated the successful application of telenephrology in rural and remote areas to reduce disparities in access to care.11 Reports from low- and middle-income countries also suggest feasibility and patient acceptance of telenephrology.12 Overall, recent evidence indicates that patient outcomes and acceptance are favorable; however, detailed protocols for implementing telenephrology remain lacking.
In our study, nephrologists were confident in managing common complications among chronic dialysis patients. In contrast, confidence in counseling scenarios was lower, likely because these interactions require trust-building and nuanced communication, which are more challenging through telehealth. Many diagnostic scenarios reached the 60% confidence threshold (e.g., urinary tract infection, ADPKD, nephrolithiasis), but management confidence lagged behind, with only UTIs and early CKD surpassing the threshold. The average diagnosis–management gap was significant. Confidence was also low for peritoneal dialysis complications, likely due to difficulties in remotely assessing catheter dysfunction and ultrafiltration failure. Follow-up after hospital discharge plays a crucial role in nephrology; however, in our study, only vaccination counseling exceeded the confidence threshold.
Our findings indicate that telenephrology may substitute for in-person visits in several common scenarios. Nephrologists reported high confidence in follow-up care for both general nephrology patients and kidney transplant recipients, particularly beyond the first-year post-transplant. However, personalized care remains essential. A recent mixed-methods study highlighted the importance of tailoring telemedicine to individual patient needs. 13 Taken together, our study provides a cross-sectional snapshot of telenephrology practice in India. Patterns are likely to evolve rapidly with the expansion of digital platforms and artificial intelligence.
This study has limitations. The sample size was modest, and findings may not be generalizable beyond India. Detailed data on specific therapies (e.g., types of immunosuppression, dialysis catheter type, and site) were not collected to avoid overburdening respondents. Rare conditions and management scenarios were excluded, as they were beyond the scope of the study. Cost-effectiveness of telenephrology was not assessed, as the primary objective was to evaluate practice patterns. Confidence was self-reported using a Likert scale, which reflects telemedicine competency but does not measure patient outcomes. Bias inherent to online surveys and variability in individual responses cannot be ruled out. Although all questions were mandatory to ensure completeness, the scope of nephrology practice varies across respondents, which may have led to skewed results in some areas (e.g., peritoneal dialysis).
This study provides a national perspective on Indian nephrologists’ confidence and readiness to manage a broad spectrum of kidney conditions through telemedicine. While confidence was high for standard diagnostic and follow-up scenarios such as AKI management and transplant surveillance, gaps remained in reproductive health, rare complications, and peritoneal dialysis–related infections. Years of clinical experience modestly influenced confidence, underscoring the need for structured, domain-specific telehealth training programs.
Our findings also highlight variability in confidence across domains, suggesting that a “one-size-fits-all” approach to telemedicine guidelines may be insufficient. Policymakers and professional societies must consider these realities while developing India-specific telemedicine frameworks for nephrology. A tailored, domain-sensitive, and experience-adapted strategy is needed to ensure equitable and effective digital nephrology services nationwide.
Article citation: Meshram HS, Gulati S, Chauhan S, Puri S, Sharma S, Bandi VK. A cross-sectional national survey on current practices and patterns in telenephrology among nephrologists. The Southwest Journal of Medicine. 2026;14(59):31–40
From: Department of Nephrology, ILBS, Vasant Kunj, New Delhi, India (HSM, SP) Department of Nephrology, Fortis Group, Delhi, India (SG, SC) Department of Nephrology, VMMC Safdarjung, New Delhi, India (SS) Department of Nephrology, Pinnamaneni Siddhartha Medical College, Andhra Pradesh, India (VKB)
Conflicts of interest: none
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