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2c9cec0112
Real-world exports were rejected wholesale (file number must be digits, sex must be M/F, every allergy/med/problem/encounter a full object), so AI imports skipped everything. Normalize at the schema edge instead: strip non-digits from the file number, map gender words to M/F, accept a bare string for allergies/medications/problems (filling sensible defaults), and default missing encounter fields (type → "Visit"). The manual patient form shares this schema and benefits too. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
125 lines
4.2 KiB
TypeScript
125 lines
4.2 KiB
TypeScript
import { z } from "zod";
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import { initialsFromName } from "./initials.js";
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const nonEmpty = z.string().trim().min(1);
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const EMPTY_VITALS = { bp: "", hr: "", temp: "", spo2: "", takenAt: "" };
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const EMPTY_TREND = { label: "", unit: "", points: [] as number[] };
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// Coerce a bare string into an object keyed on its primary field, so a sparse
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// export ("Penicillin", "Metformin") still validates — both the AI import and
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// the patient form benefit. Real objects pass through untouched.
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const stringToObject = (key: string) => (value: unknown) =>
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typeof value === "string" ? { [key]: value } : value;
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export const allergySchema = z.preprocess(
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stringToObject("substance"),
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z.object({
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substance: nonEmpty,
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reaction: z.string().default(""),
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severity: z.enum(["mild", "moderate", "severe"]).default("mild"),
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}),
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);
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export const medicationSchema = z.preprocess(
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stringToObject("name"),
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z.object({
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name: nonEmpty,
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dose: z.string().default(""),
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frequency: z.string().default(""),
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}),
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);
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export const problemSchema = z.preprocess(
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stringToObject("label"),
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z.object({
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label: nonEmpty,
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since: z.string().default(""),
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}),
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);
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export const labSchema = z.object({
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name: nonEmpty,
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value: nonEmpty,
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flag: z.enum(["normal", "high", "low", "critical"]).default("normal"),
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takenAt: z.string().default(""),
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});
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export const encounterSchema = z.object({
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date: z.string().default(""),
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// A visit row always has a department/type, but never let it be empty.
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type: z
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.string()
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.default("")
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.transform((s) => s.trim() || "Visit"),
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provider: z.string().default(""),
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summary: z.string().default(""),
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});
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export const vitalsSchema = z.object({
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bp: z.string(),
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hr: z.string(),
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temp: z.string(),
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spo2: z.string(),
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takenAt: z.string(),
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});
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export const trendSchema = z.object({
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label: z.string(),
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unit: z.string(),
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points: z.array(z.number()),
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});
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// A full patient payload — the frontend form sends the entire record on both
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// create and edit, so the same schema covers both.
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//
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// Tolerant by design: an AI import from a sparse export (e.g. just a name) still
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// validates. The file number may be empty (the patient service auto-generates
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// one), demographics fall back to safe placeholders, initials are derived from
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// the name, and the clinical sections default to empty. Such rows are stamped
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// `source: "ai"` and surfaced with an "Added by AI" badge for later editing.
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export const patientInputSchema = z
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.object({
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// Real-world exports use IDs like "P00001"; keep only the digits (empty ⇒
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// the patient service auto-generates one). Never reject on stray letters.
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fileNumber: z.preprocess(
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(v) => (typeof v === "string" ? v.replace(/\D/g, "") : v),
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z.string().trim().default(""),
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),
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name: nonEmpty,
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age: z.coerce.number().int().min(0).max(150).default(0),
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// Accept gender words (Male / female / man / F / …), not just M/F.
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sex: z.preprocess((v) => {
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if (typeof v !== "string") return v;
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const s = v.trim().toLowerCase();
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if (s.startsWith("m")) return "M";
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if (s.startsWith("f") || s.startsWith("w")) return "F";
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return v;
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}, z.enum(["M", "F"]).default("M")),
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pcp: z.string().default(""),
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// Optional link to the responsible clinician (user id). Empty string ⇒ null.
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primaryProviderId: z.preprocess(
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(v) => (v === "" ? null : v),
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z.string().nullable().optional(),
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),
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status: z.enum(["active", "inpatient", "discharged"]).default("active"),
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initials: z.string().trim().max(4).default(""),
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allergies: z.array(allergySchema).default([]),
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alerts: z.array(z.string()).default([]),
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medications: z.array(medicationSchema).default([]),
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problems: z.array(problemSchema).default([]),
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vitals: vitalsSchema.default(EMPTY_VITALS),
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vitalsTrend: trendSchema.default(EMPTY_TREND),
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labs: z.array(labSchema).default([]),
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labTrend: trendSchema.default(EMPTY_TREND),
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encounters: z.array(encounterSchema).default([]),
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source: z.enum(["manual", "ai"]).default("manual"),
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})
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.transform((v) => ({
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...v,
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initials: v.initials || initialsFromName(v.name),
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}));
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export type PatientInput = z.infer<typeof patientInputSchema>;
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