Table 2. Number of articles per category after the final iterative review through the literature.

Category	Description of a need for or the creation of an algorithm to detect or a data model for…	Number of articles (citations)
Adverse events	The potential for or the occurrence of unexpected and/or undesirable medical events such as drug allergies, drug side effects, falls, unexpected diseases, or other treatment-related injury	22 13 14 15 16 17 18 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97
Clinician cognitive processes	The clinician's reasons for decisions made in the EHR regarding patient care, including alert overrides and handoffs	12 19 20 21 22 23 98 99 100 101 102 103 104
Data standards creation and data communication	Storage of data for medical fields or aspects of medical fields in a standard medical format (e.g., HL7, C-CDA, or an author-specific format) or mapping of data models of commonly used resources (e.g., Web sites or apps) to standard medical data formats for the purpose of EHR interoperability among other EHRs and external applications	29 24 25 26 27 28 29 30 31 32 33 34 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122
Genomics	Patient genetic information including WGS, whole-exome, SNP, and other genetic data from other tests not listed. The genetic data can be utilized for the purpose of diagnosis, prescription (pharmacogenomic information), or other medically relevant purposes	12 35 36 37 38 39 40 41 123 124 125 126 127
Medication list data capture	More robust medication data storage (e.g., medications prescribed by other hospitals, medication and/or illicit drug abuse information), including additional drug metadata (e.g., adherence to medication schedule) that would allow clinicians to easily determine patients' medication status along with storage of patient medication information in medication list rather than free text	14 42 43 44 45 46 47 48 49 50 51 52 53 54 128
Patient preferences	Storage of patient's desires for treatment, therapy, or lack thereof for health events such as end-of-life care, diseases, or AEs	2 57 129
Patient-reported data	An outcome of a health event (e.g., disease, risk factor) or therapy (medication schedule, treatment plan) that is reported by and directly relatable to the patient. Quantification is sometimes done through the abstract score of quality of life. Patient-reported data may not be correlated with medically defined outcomes (increased FEV 1 in COPD patients does not always result in improved QOL for a patient)	13 58 59 60 61 62 63 64 130 131 132 133 134 135
Phenotyping	Identifying a specific, medically relevant, physical characteristic (e.g., disease state, current treatment, or physical trait) by utilizing the presence of clinical data in the medical record (e.g., laboratory test results, clinical notes analyzed through NLP, or physical exam findings)	61 13 14 15 16 17 18 20 24 25 31 32 35 41 42 43 45 46 60 64 66 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187

Note: The categories and their definition of data content described in the literature that could be used to expand the EHR.