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In the mid-1980s, RAND Corporation and University of California Los Angeles (UCLA) developed the RAND/UCLA Appropriateness Method (RAM) to evaluate the correctness of medical and surgical procedures. In this study, the RAND/UCLA Appropriateness Method was used to evaluate the appropriateness of a dataset concerning kidney transplantation in adult and pediatric recipients for an information system funded by the Italian Ministry of Health. The original dataset was obtained using an interdisciplinary pool of regional experts (n = 60). This dataset held 514 items about kidney transplantation in adult (n = 268) and pediatric (n = 246) recipients. The items were stratified as 3 main groups: pretransplantation items (adult, n = 141; pediatric, n = 122), transplantation items (adult, n = 49; pediatric, n = 45), and early posttransplantation and follow-up items (adult, n = 78; pediatric, n = 79). In the second round, the dataset was subjected to an extraregional panel of independent experts (n = 9) to assess each item using a score ranging from 1 to 9 based on increasing appropriateness. The expert-opinion process returned for adult and pediatric kidney recipient items whole mean scores of 8.52 ± 0.32 and 8.65 ± 0.32, respectively. Overall agreement, uncertainty, and disagreement between experts about item appropriateness concerning adult kidney recipients were 94.6%, 5.4%, and 0%, respectively. For pediatric kidney recipients, overall agreement, uncertainty, and disagreement between experts about item appropriateness were 96.9%, 2.35%, and 0.07%, respectively. This study supported the use of a structured expert-opinion process as an effective strategy to evaluate the appropriateness of large datasets for kidney transplantation in both adult and pediatric recipients.

With the aim to evaluate the correctness of medical and surgical procedures, RAND Corporation and University of California Los Angeles (UCLA) developed the RAND/UCLA Appropriateness Method (RAM). In this study, the RAM was applied to evaluate the appropriateness of a dataset concerning kidney/pancreas transplantation in adult recipients for an information system funded by the Italian Ministry of Health. The original dataset was obtained using an interdisciplinary pool of experts (n = 60) involved in kidney/pancreas transplantation activity in the Liguria Region. This dataset held 291 items, stratified as pretransplantation items (n = 158), transplantation items (n = 49), and early posttransplantation and follow-up items (n = 84). In the second round, the dataset was subjected to an extraregional panel of independent experts (n = 9) to assess each item using a score ranging from 1 to 9 based on increasing appropriateness. The expert-opinion process returned a whole mean score of 8.47 ± 0.43 (95% confidence interval [CI] 8.30–8.63). Overall agreement, uncertainty, and disagreement between experts about item appropriateness were 98.5%, 1.49%, and 0%, respectively. Agreement/uncertainty for pretransplantation, transplantation, and posttransplantation items were 99.87%/0.12%, 100%/0%, and 96.37%/3.62%, respectively. This study supported the utility of a structured expert-opinion process as an effective strategy to evaluate the appropriateness of large datasets for kidney/pancreas transplantation in adult recipients.

The Delphi Method (DM) is the most frequently used technique to acquire structured expert-opinion elicitation (EOE). It has been increasingly applied to construct guidelines in medicine and to evaluate the appropriateness of clinical procedures. In this study, the RAND/UCLA appropriateness method was used as a structured EOE process to evaluate the appropriateness of a dataset concerning liver transplantation in adult and pediatric recipients for an information system funded by the Italian Ministry of Health. The original dataset was obtained using an interdisciplinary pool of regional experts (n = 60). This dataset held 280 items stratified into three groups: I. pretransplant items (n = 123); II. transplant items (n = 65); III. early posttransplant and follow-up items (n = 92). In the second DM round, the dataset was subjected to an extraregional panel of independent experts (n = 9) to assess a score ranging from 1 to 9 on each item based on increasing appropriateness, according to the RAND/UCLA Appropriateness Method. Overall agreement, uncertainty, and disagreement between experts was 95.89%, 3.12%, and 0.99%, respectively. For each group, agreement-uncertainty-disagreement were 99.35%/0.65%/0% (group I), 91.53%/5.30%/3.17% (group II), and 96.87%/3.13%/0% (group III), respectively. This study supported the use of a structured EOE process to evaluate the appropriateness of a large dataset for liver transplantation activity.

Expert-opinion elicitation (EOE) is a heuristic process for gathering evidence and data or answering questions on issues/problems of concern. The Delphi method (DM) is the most frequent technique used to obtain structured elicitation of expert opinions. It has been increasingly applied in medicine to produce guidelines and to evaluate the appropriateness of diagnostic procedures. In this study, a DM has been used as structured EOE process to assess the appropriateness and clinical priority of a data set-based informative system in the context of the Liguria-Trento Transplant Network (LTTN) Project, funded by Italian Ministry of Health. The original data set was obtained by using an interdisciplinary pool of regional experts (n = 60). This data set held 1506 items stratified in 21 categories at various surgical phases (preoperative, intraoperative, and postoperative) and transplantation types (liver, kidney, and kidney/pancreas) in adult and pediatric recipients. Some categories included cadaveric donor management, organ allocation, and acute liver failure. In the second DM round, the data set was subjected to a panel of extraregional, independent experts (n = 9) to assess scores ranging from 1 to 9 on each item, based on increasing appropriateness/priority, according to RAND/UCLA Appropriateness Method. The overall agreement between experts was 95.88%, whereas disagreement and uncertainty were 0.13% and 3.98%, respectively. A major uncertainty occurred for the data set concerning the multiorgan cadaveric donor, for liver transplantation, and for kidney transplantation in adult recipients. The use of a structured EOE process may represent an effective strategy to define the appropriateness and prioritization criteria of a large data set in the field of solid organ transplantation.

In Italy, health-care telematic is funded and supported at the level of national government or regional institutions. In 1999, the Italian Ministry of Health started to fund the Liguria-Trento Transplant Network (LTTN) project, a health research project with the aim to build an informative system for donor management and transplantation activity in a macroregional area. At the time of LTTN project proposal, no published Transplant Network Informative System fulfilled Italian rules on telematic management of electronic documentation concerning transplantation activity. Partnership of LTTN project were two Regional Transplant Coordinating Centres, Nord Italia Transplant Interregional Coordinating Centre and the Italian Institute of Health/National Transplant Coordinating Centre. Project Total Quality Management methods were adopted. Technological and case analysis followed ANSI-HL7, CEN-TC251, and Object-Oriented Software Engineering standards. A low-tech prototype powered by a web access relational database is running on a transplant network including web-based clients located in 17 intensive care units, in Nord Italia Transplant Interregional Coordinating Centre, and at the Italian Institute of Health/National Transplant Coordinating Centre. LTTN registry includes pretransplant, surgical, and posttransplant phases regarding liver, kidney, pancreas, and kidney-pancreas transplantation in adult and pediatric recipients. Clinical specifications were prioritized in agreement with the RAND/UCLA appropriateness method. Further implementation will include formal rules for data access and output release, fault tolerance, and a continuous registry evolution plan.