Development, Design and Utilization of a CDSS for Refeeding Syndrome in Real Life Inpatient Care—A Feasibility Study

Background: The refeeding syndrome (RFS) is an oftentimes-unrecognized complication of reintroducing nutrition in malnourished patients that can lead to fatal cardiovascular failure. We hypothesized that a clinical decision support system (CDSS) can improve RFS recognition and management. Methods: We developed an algorithm from current diagnostic criteria for RFS detection, tested the algorithm on a retrospective dataset and combined the final algorithm with therapy and referral recommendations in a knowledge-based CDSS. The CDSS integration into clinical practice was prospectively investigated for six months. Results: The utilization of the RFS-CDSS lead to RFS diagnosis in 13 out of 21 detected cases (62%). It improved patient-related care and documentation, e.g., RFS-specific coding (E87.7), increased from once coded in 30 month in the retrospective cohort to four times in six months in the prospective cohort and doubled the rate of nutrition referrals in true positive patients (retrospective referrals in true positive patients 33% vs. prospective referrals in true positive patients 71%). Conclusion: CDSS-facilitated RFS diagnosis is possible and improves RFS recognition. This effect and its impact on patient-related outcomes needs to be further investigated in a large randomized-controlled trial.

[1]  M. Stumvoll,et al.  Refeeding Syndrome—Diagnostic Challenges and the Potential of Clinical Decision Support Systems. , 2023, Deutsches Arzteblatt international.

[2]  M. Drainoni,et al.  The impact of clinical decision support systems on provider behavior in the inpatient setting: A systematic review and meta-analysis. , 2022, Journal of hospital medicine.

[3]  J. Yamada,et al.  Do providers use computerized clinical decision support systems? A systematic review and meta-regression of clinical decision support uptake , 2022, Implementation Science.

[4]  Yu Hong,et al.  Association Between Admission Serum Phosphate Level and All-Cause Mortality Among Patients with Spontaneous Intracerebral Hemorrhage , 2021, Risk management and healthcare policy.

[5]  E. Ghigo,et al.  The incidence of the refeeding syndrome. A systematic review and meta-analyses of literature. , 2021, Clinical nutrition.

[6]  E. Ghigo,et al.  Impact of refeeding syndrome on short- and medium-term all-cause mortality: a systematic review and meta-analysis. , 2021, The American journal of medicine.

[7]  C. Baerwald,et al.  Refeeding-Syndrom , 2020, Zeitschrift für Rheumatologie.

[8]  S. Bo,et al.  The Refeeding Syndrome: a neglected but potentially serious condition for inpatients. A narrative review , 2020, Internal and Emergency Medicine.

[9]  K. Shojania,et al.  Computerised clinical decision support systems and absolute improvements in care: meta-analysis of controlled clinical trials , 2020, BMJ.

[10]  C. Cundius,et al.  The Clinical Decision Support System AMPEL for Laboratory Diagnostics: Implementation and Technical Evaluation , 2020, JMIR medical informatics.

[11]  F sadoughi,et al.  The effects of clinical decision support system for prescribing medication on patient outcomes and physician practice performance: a systematic review and meta-analysis , 2020, BMC Medical Informatics and Decision Making.

[12]  A. Kribben,et al.  The Effects of Intensive Versus Routine Treatment in Patients with Acute Kidney Injury. , 2020, Deutsches Arzteblatt international.

[13]  G. Sacks,et al.  ASPEN Consensus Recommendations for Refeeding Syndrome. , 2020, Nutrition in clinical practice : official publication of the American Society for Parenteral and Enteral Nutrition.

[14]  F. Gomes,et al.  Refeeding syndrome is associated with increased mortality in malnourished medical inpatients , 2020, Medicine.

[15]  C. Kruse,et al.  Effects of Computerized Decision Support Systems on Practitioner Performance and Patient Outcomes: Systematic Review , 2019, JMIR medical informatics.

[16]  R. Irizarry.  ggplot2 , 2019, Introduction to Data Science.

[17]  M. Crook,et al.  Disorders of phosphate metabolism , 2019, Journal of Clinical Pathology.

[18]  D. Volkert,et al.  The Refeeding Syndrome revisited: you can only diagnose what you know , 2019, European Journal of Clinical Nutrition.

[19]  Christophe Zemmour,et al.  Impact of a computer-assisted decision support system (CDSS) on nutrition management in critically ill hematology patients: the NUTCHOCO study (nutritional care in hematology oncologic patients and critical outcome) , 2019, Annals of Intensive Care.

[20]  P. Schütz,et al.  Refeeding-Syndrom: Ein konsensusbasierter Algorithmus für stationäre Patienten , 2019, Aktuelle Ernährungsmedizin.

[21]  C. Jurkovitz,et al.  Characteristics and Outcomes of Adult Inpatients With Malnutrition , 2018, JPEN. Journal of parenteral and enteral nutrition.

[22]  Julian Varghese,et al.  Effects of computerized decision support system implementations on patient outcomes in inpatient care: a systematic review , 2018, J. Am. Medical Informatics Assoc..

[23]  M. Pourhassan,et al.  Refeeding-Syndrom , 2018, Der Internist.

[24]  R. Kressig,et al.  Management and prevention of refeeding syndrome in medical inpatients: An evidence-based and consensus-supported algorithm. , 2018, Nutrition.

[25]  D. Kershenobich,et al.  Electrolyte and Acid–Base Disturbances in End-Stage Liver Disease: A Physiopathological Approach , 2017, Digestive Diseases and Sciences.

[26]  Hadley Wickham,et al.  ggplot2 - Elegant Graphics for Data Analysis (2nd Edition) , 2017 .

[27]  P. Schuetz,et al.  Revisiting the refeeding syndrome: Results of a systematic review. , 2017, Nutrition.

[28]  J. Dyson,et al.  Adult parenteral nutrition in the North of England: a region-wide audit , 2017, BMJ Open.

[29]  C. Siegert,et al.  Incidence of refeeding syndrome in internal medicine patients. , 2016, The Netherlands journal of medicine.

[30]  L. Moja,et al.  Effectiveness of computerized decision support systems linked to electronic health records: a systematic review and meta-analysis. , 2014, American journal of public health.

[31]  Steen Andreassen,et al.  Decision support for optimized blood glucose control and nutrition in a neurotrauma intensive care unit: preliminary results of clinical advice and prediction accuracy of the Glucosafe system , 2012, Journal of Clinical Monitoring and Computing.

[32]  A. Culkin,et al.  Refeeding hypophosphataemia is more common in enteral than parenteral feeding in adult in patients. , 2011, Clinical nutrition.

[33]  L. Barker,et al.  Hospital Malnutrition: Prevalence, Identification and Impact on Patients and the Healthcare System , 2011, International journal of environmental research and public health.

[34]  M. Crook,et al.  Refeeding syndrome: treatment considerations based on collective analysis of literature case reports. , 2010, Nutrition.

[35]  R. Kumar,et al.  Mechanisms of Renal Phosphate Loss in Liver Resection-Associated Hypophosphatemia , 2009, Annals of surgery.

[36]  D. Lobo,et al.  Nutrition in clinical practice—the refeeding syndrome: illustrative cases and guidelines for prevention and treatment , 2008, European Journal of Clinical Nutrition.

[37]  H. Datta,et al.  Hepatic surgery-related hypophosphatemia. , 2007, Clinica chimica acta; international journal of clinical chemistry.

[38]  Dorothee Volkert,et al.  The German hospital malnutrition study. , 2006, Clinical nutrition.

[39]  H. Mcdonald,et al.  Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. , 2005 .

[40]  J. Kondrup,et al.  Nutritional risk screening (NRS 2002): a new method based on an analysis of controlled clinical trials. , 2003, Clinical nutrition.

[41]  L. Dimeglio,et al.  Disorders of phosphate metabolism. , 2000, Endocrinology and metabolism clinics of North America.

[42]  K. Polderman,et al.  Hypomagnesemia and hypophosphatemia at admission in patients with severe head injury , 2000, Critical care medicine.

[43]  K. Nepple,et al.  Malnutrition Diagnosis during Adult Inpatient Hospitalizations: Analysis of a Multi-Institutional Collaborative Database of Academic Medical Centers. , 2018, Journal of the Academy of Nutrition and Dietetics.

[44]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[45]  Cedric E. Ginestet.  ggplot2: Elegant Graphics for Data Analysis , 2011 .